{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's make things pretty!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Color! Texture! Style! Not only do we want to make our plots aesthetically appealing, we often want to show more than just one or two variables on our plot. Cartographer Jacques Bertin developed the following recommendations for encoding visual information (and yes, Matplotlib supports all of these visual encodings):"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "![table describing how points, lines, and area can be encoded with different attributes such as shape, size, hue, value, and intensity to show differences in the data](../images/retinal-variables.png)\n",
    "\n",
    "J. Krygier and D. Wood, Making Maps: A Visual Guide to Map Design for GIS, 1 edition. New York: The Guilford Press, 2005.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# New notebook, same imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The titanic dataset has no continuous data, so here we demonstrate manipulating a line plot using sine waves. We use the numpy library to generate our sine and cosine waves. Here the x values are 1000 values equally spaced between 0 and 2$\\pi$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's make a line plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "x = np.linspace(0,2*np.pi, 100)\n",
    "sin_x = np.sin(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAD4CAYAAADhNOGaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nO3dd3yV9fn/8deVRSAkzARCAgTIgACyIoIDZQqoRa21YrX4ayu1guKoLVVrbWvrqrbVIoqAYh04caKgDGXICMieIRASZliBELKv3x85+E1jgIRzkvuM6/l4nEfOvc79DiNXPvf9uT8fUVWMMcYEriCnAxhjjHGWFQJjjAlwVgiMMSbAWSEwxpgAZ4XAGGMCXIjTAc5Hy5YtNSEhwekYxhjjU1atWnVIVaOrrvfJQpCQkEB6errTMYwxxqeISFZ16+3SkDHGBDgrBMYYE+CsEBhjTICzQmCMMQHOCoExxgQ4jxQCEZkuIgdFZMMZtouIPCciGSKyTkR6V9o2XES2urZN9EQeY4wxNeepFsGrwPCzbB8BJLleY4HJACISDExybU8FRotIqocyGWOMqQGPPEegqt+ISMJZdhkFvKYVY14vE5GmIhILJAAZqpoJICIzXftu8kQuUzuFJWVk5p5k+8ETHDlZTFFpOUUl5YSGCDGR4cRENiChRQRtmzdERJyOa4zxkPp6oCwOyK60nONaV936i6r7ABEZS0Vrgnbt2tVNygBTXFpOetYRFm7NZeHWg2w/mE9Npqdo2TiMXu2a0a9jC66+IJZWUeF1H9YYU2fqqxBU9+ujnmX9D1eqTgGmAKSlpdlsOm7IPlLA68uyeDs9m2MFJYQGCxd1aMGIbrEktWpMYkxjYiLDCQ8NIiw4iKLScnJPFHHwRBEZB/NZlXWUVVlH+HLTAR77bBMXd2rB9b3iuaZHG8JCrP+BMb6mvgpBDtC20nI8sBcIO8N6Uwc27zvOM3O3MW/LAYJEGJbaimt7xXFJYksaNzjzP4WQ4CAiGoSQ0DKCvh2ac/NFFS2yHbn5fLRmLx+t2cP9767lmblbGTugIzf1bUd4aHB9fVvGGDeJp6aqdN0j+FRVu1Wz7SpgPDCSiks/z6lqXxEJAbYBg4E9wErgZlXdeLZzpaWlqY01VHN7jp3imblbmfXdHqLCQxnTvz2jL2pHbJOGHvl8VeWb7YeYND+DFbuOEB3ZgD+M6Mx1veLsXoIxXkREVqlqWtX1HmkRiMhbwBVASxHJAf4EhAKo6ovAbCqKQAZQAPw/17ZSERkPzAGCgennKgKm5srKlVeW7OTpOVtRYOxlHbnzikSaNAr16HlEhMuTo7k8OZrlmYd5/PMt3PfOWmauzOavo7qR0jrSo+czxniWx1oE9claBOeWmZvPA++tY1XWUYZ0ieHPo7oR19QzLYBzKS9X3k7P5skvtpBfWMpvr0xh7GUdCQqy1oExTqrTFoHxLu+vyuGhD9fTICSYf/60B9f2rN9LNEFBwui+7biya2se/nA9T3y+hSUZh3jmxh7ERFoPI2O8jXXx8CPFpeU88tEG7n93LT3bNmXuvQO4rle8Y9fpm0eEMenm3jx+fXdW7jrCyH8vYsXOI45kMcacmRUCP3Eov4jRLy/jtW+zuP2yDrz+y4u8on+/SEXr4JPxlxIVHsotU5fzweocp2MZYyqxQuAHso8UcMPkpWzcm8fzo3vx0FWphAR7119tUqtIZt15CX3aN+O+d9byjzlbKS/3vftTxvgj7/ppYWpt4948rp+8lKMFJbzxq35c06ON05HOqEmjUGb8oi8/TWvLfxZk8OCs9ZRZMTDGcXaz2IetyjrCbdNX0jg8hDfv6E9SK+/vphkWEsQTP+5OTFQDnp+fQWFJGf/4SQ+va8EYE0isEPio1buPMmb6SqIjG/DGry6iTT11DfUEEeH+YSmEhwbz9JytFJWW8++betnwFMY4xP7n+aB1OccYM20FLRqH8dbt/XyqCFQ2bmAif7w6lc837Ofed9bYZSJjHGItAh+zae9xbpm6nCaNQnnz9n60buJ8zyB3/PLSDpSXK3+bvZmo8FD+fl03G5bCmHpmhcCH5Bwt4LZXVhDRIIS3bu9Xb08K17XbB3Tk2KliJi3YQdNGofx+eGenIxkTUKwQ+Ii8ghJue2Ulp0rKeO+Oi2nbvJHTkTzqt8NSOFZQwuSFO2jZuAG/vLSD05GMCRhWCHxAYUkZt7+Wzu7DBcz4RV+/HMRNRPjLqG4cOVnMY59tIqFFIwZ3aeV0LGMCgt0s9nKqyh8+WM+KXUf4x4096N+phdOR6kxwkPDsjT3p1qYJd731HZv2Hnc6kjEBwQqBl5u2eCezvtvD/UOT+ZEXPyzmKQ3Dgpk6Jo2o8FB+NWMlB48XOh3JGL9nhcCLLdqey99nb2ZEt9aMH5TodJx60yoqnKlj0jhaUMKdb6ympKzc6UjG+DUrBF4q6/BJxr/5HcmtIvnHT3oEXJfKbnFNePKGC0jPOsrjs7c4HccYv+aRQiAiw0Vkq4hkiMjEarY/ICJrXK8NIlImIs1d23aJyHrXNptthoqbw795fTUAU25NI+Is8wn7sx/1aMNtFycwfclOPl1nU1kbU1fcLgQiEgxMAkYAqcBoEUmtvI+qPq2qPVW1J/AH4GtVrTww/UDX9h/MnBOIHvtsE5v2HefZG3vQroV/dROtrQdHdqFP+2b87r11bD9wwuk4xvglT7QI+gIZqpqpqsXATGDUWfYfDbzlgfP6pU/X7eX1ZbsZO6CjdZ+kYpC6F37Wm0ZhwYx7czWFJWVORzLG73iiEMQB2ZWWc1zrfkBEGgHDgfcrrVZgroisEpGxZzqJiIwVkXQRSc/NzfVAbO+z69BJJr6/nl7tmvLAlSlOx/EaraLCefbGnmw7kM/fPtvsdBxj/I4nCkF1dzHPNHrYNcCSKpeFLlHV3lRcWhonIgOqO1BVp6hqmqqmRUdHu5fYC5WUlTNh5ncEBwn/ubk3oTYs8/8YkBzN7Zd14L/Lspi7cb/TcYzxK574aZMDtK20HA+c6c7eTVS5LKSqe11fDwKzqLjUFHCen5/B2pw8Hr++u9+MIeRpv70yha5tovjd++vYl3fK6TjG+A1PFIKVQJKIdBCRMCp+2H9cdScRaQJcDnxUaV2EiESefg8MAzZ4IJNPWb37KJMWZHB97zhGdo91Oo7XahASzHOje1FUUs5v311rU10a4yFuFwJVLQXGA3OAzcA7qrpRRO4QkTsq7XodMFdVT1Za1wpYLCJrgRXAZ6r6hbuZfMnJolLufXsNraPCefRHXZ2O4/U6RTfm4au7sCTjMG8sz3I6jjF+wSMd1FV1NjC7yroXqyy/CrxaZV0m0MMTGXzV32ZvZveRAt4e25+o8FCn4/iEm/u244sN+/n77C1clhRNQssIpyMZ49PsjqSDlmQc4s3lu7n9so707dDc6Tg+Q0R46oYLCAkWHnhvrc1sZoybrBA45GRRKb9/fx0dW0Zw39Bkp+P4nNgmDXn0mq6s3HWUV5bsdDqOMT7NCoFDnp6zlT3HTvHUDRcQHhrsdByfdH3vOIZ0acU/5m4l6/DJcx9gjKmWFQIHrNh5hFeX7mJM/wTSEuyS0PkSER67thuhQUE8OGs9qnaJyJjzYYWgnhWVljHx/XW0bd6Q3w23p4fd1bpJOL8f0ZklGYd5b1WO03GM8UlWCOrZ5IU7yDx0kr9d251GYYE5qqin3dy3HRcmNOOxzzaTe6LI6TjG+BwrBPVoR24+LyzYwY96tGFAsv8Nk+GUoCDh8esv4FRxGX/+ZKPTcYzxOVYI6omq8tCs9YSHBvHw1V2cjuN3EmMaM25gIp+u28ei7f45KKExdcUKQT15f/UelmUeYeKILsREhjsdxy/9+vKOJLRoxCMfbaSo1IarNqamrBDUg7yCEv4+ezO92zXlpgvbnvsAc17CQ4P5y6hu7Dx0kilfZzodxxifYYWgHjz75VaOFRTz2LXdCQoKrLmH69uA5Giu6h7LfxZkkH2kwOk4xvgEKwR1bNPe4/x3WRa39mtPapsop+MEhD9enUpIkPDox3bj2JiasEJQh1SVP328gaaNwrhvqD0zUF9aNwlnwpAk5m05yIItB52OY4zXs0JQhz5cs4eVu47y++EpNGlkI4vWp9su7kDHlhH89dNNFJeWOx3HGK9mhaCO5BeV8vfZW+jRtik/6WM3iOtbWEgQf7wmlcxDJ3l1qQ1KZ8zZeKQQiMhwEdkqIhkiMrGa7VeISJ6IrHG9Hqnpsb5q8sIMck8U8eg1qXaD2CEDU2IY1DmG5+ZlcPBEodNxjPFabhcCEQkGJlEx+XwqMFpEUqvZdZGq9nS9/lLLY31K9pECXl60k+t6xdGrXTOn4wS0P16dSlFpGU9/sdXpKMZ4LU+0CPoCGaqaqarFwExgVD0c67We+HwLwSI2qJwX6NAygl9c0oF3V+WwYU+e03GM8UqeKARxQHal5RzXuqr6i8haEflcRE5PzlvTY33Gip1H+Gz9Pu64vBOxTRo6HccA4wYl0jwijMc+22RDVRtTDU8UguougFf937YaaK+qPYDngQ9rcWzFjiJjRSRdRNJzc71zLJnycuUvn24ktkk4Ywd0dDqOcYkKD+XeIUksyzzCl5sOOB3HGK/jiUKQA1TuFhMP7K28g6oeV9V81/vZQKiItKzJsZU+Y4qqpqlqWnS0d47c+eGaPWzYc5zfDU+hYZjNOuZNRvdtR2JMYx7/fIt1JzWmCk8UgpVAkoh0EJEw4Cbg48o7iEhrERHX+76u8x6uybG+orCkjH/M2Uq3uChG9fDpq1t+KSQ4iIdGdmHnoZO8sTzL6TjGeBW3C4GqlgLjgTnAZuAdVd0oIneIyB2u3W4ANojIWuA54CatUO2x7mZywitLdrE3r5AHR3ax7qJe6oqUaC5NbMm/vtpOXkGJ03GM8RriizfP0tLSND093ekY3ztyspjLn1pA3w7NmXbbhU7HMWexae9xrnp+EWMHdOQPI2xeCBNYRGSVqqZVXW9PFnvAc/O2c7K4lIkjOjsdxZxDapsorusZV9GCO3bK6TjGeAUrBG7KOlxxzfmnF7YjqVWk03FMDdw3LBkUnv1ym9NRjPEKVgjc9MzcbYQEBXHvkCSno5gaim/WiDEXt+f91Tls2X/c6TjGOM4KgRs27Mnj47V7+cWlCcRE2fSTvmTcwEQiG4TwlA09YYwVAnc8NWcrTRuF8uvLOzkdxdRS00Zh3DkwkflbDrI887DTcYxxlBWC87R0xyG+2ZbLuCsSiQq3uQZ80W0XJ9AqqgFPzdlqQ0+YgGaF4DyoKk9+sZU2TcK5tX97p+OY8xQeGsyEwcmsyjrKfJvJzAQwKwTnYc7GA6zNPsY9Q5IJD7WhJHzZT9LiSWjRiKfnbKW83FoFJjBZIailsnLl2S+30jE6gut721ASvi40OIj7hqWwZf8JPllX7TBXxvg9KwS19PHaPWw7kM/9Q1MICbY/Pn9wdfdYUmOjeGbuNhuQzgQk+0lWCyVl5fzzy+2kxkYxoltrp+MYDwkKEh64MoXdRwp4b1WO03GMqXdWCGrhnfRsdh8p4IErU2xgOT9zRUo0fdo34/n52yksKXM6jjH1ygpBDRWWlPHcvO30ad+MK1K8cz4Ec/5EhPuHJbMvr5A3l+92Oo4x9coKQQ29viyLA8eL+O2wFFxTKxg/c3GnllzcqQUvLMygoLjU6TjG1BsrBDVQUFzKi1/v4JLEFvTv1MLpOKYO3T8smUP5xcxYapPXmMBhhaAGXvs2i0P5xdw3NNnpKKaO9WnfnIEp0bz49Q6OF9rkNSYweKQQiMhwEdkqIhkiMrGa7T8TkXWu11IR6VFp2y4RWS8ia0TEe2abcckvKuWlr3dweXI0fdo3dzqOqQf3DU0h71QJryze5XQUY+qF24VARIKBScAIIBUYLSKpVXbbCVyuqhcAfwWmVNk+UFV7VjdzjtNeWbyTowUl1hoIIN3jmzA0tRVTF2eSd8paBcb/eaJF0BfIUNVMVS0GZgKjKu+gqktV9ahrcRkQ74Hz1rm8UyW8vCiTIV1a0aNtU6fjmHp0z5AkThSWMm3xTqejGFPnPFEI4oDsSss5rnVn8kvg80rLCswVkVUiMvZMB4nIWBFJF5H03NxctwLX1PTFOzleWMq9Q23SmUDTtU0ThndtzSuLd3KsoNjpOMbUKU8Ugur6UlY7epeIDKSiEPy+0upLVLU3FZeWxonIgOqOVdUpqpqmqmnR0XXfjz+voITpi3cyvGtrurZpUufnM97nnqFJnCgqZeoiaxUY/+aJQpADtK20HA/8YPQuEbkAmAqMUtXvZwJR1b2urweBWVRcanLctMWZnCgqZYJNQRmwOreO4qrusbyyZCdHTlqrwPgvTxSClUCSiHQQkTDgJuDjyjuISDvgA+BWVd1WaX2EiESefg8MAzZ4IJNbjhUU88qSXYzo1pousVFOxzEOmjAkiYKSMqYuynQ6ijF1xu1CoKqlwHhgDrAZeEdVN4rIHSJyh2u3R4AWwAtVuom2AhaLyFpgBfCZqn7hbiZ3TVu8kxNFpdw92FoDgS65VSRXdY9lxtJd1iowfivEEx+iqrOB2VXWvVjp/a+AX1VzXCbQo+p6J51uDYzsbq0BU+HuwUl8tn4fUxdl8rvhnZ2OY4zH2ZPFVUxbvJN8aw2YSiq3Co5aq8D4ISsElVRuDXRuba0B83/uHuy6V7DY7hUY/2OFoJLp1howZ3C6VfDqEmsVGP9jhcAlr6CEV5bsYnhXaw2Y6lmrwPgrKwQu05dYTyFzdsmtIhnZLZYZS7PsaWPjV6wQUDGm0PQlOxmW2orUNtYaMGd21+BE8otKmW5jEBk/YoUAmLF0FycKrTVgzq1z66iKMYiW7LKRSY3fCPhCcKKwhGmLdzKkSyu6xdmYQubc7hqcyImiUl5ZYq0C4x8CvhC89m0WeadKuHtwotNRjI/o2qZivoKK0WmtVWB8X0AXgpNFpUxdlMnAlGguiLf5BkzNTRicxPHCUmYs2eV0FGPcFtCF4PVlWRwtKLF7A6bWusU1YXDnGKYtqXj2xBhfFrCF4FRxGVO+yWRAcjS92jVzOo7xQXcNTuJYQQn//TbL6SjGuCVgC8Eby7M4fLKYCXZvwJynnm2bcnlyNFMXZVJQbK0C47sCshAUlpTx0jeZXNypBX3aN3c6jvFhdw9O4vDJYt5cvtvpKMact4AsBG+vzCb3RJHdGzBu69O+GZcktuDFrzMpLClzOo4x5yXgCkFRaRmTF+6gb0Jz+nVs4XQc4wfuHpTEofwi3lphrQLjmzxSCERkuIhsFZEMEZlYzXYRkedc29eJSO+aHutp76bnsP94obUGjMdc1LEFF3VozktfZ1JUaq0C43vcLgQiEgxMAkYAqcBoEUmtstsIIMn1GgtMrsWxHlNcWs7khTvo1a4plyRaa8B4zt2Dk9h/vJB303OcjmJMrXmiRdAXyFDVTFUtBmYCo6rsMwp4TSssA5qKSGwNj/WYWd/lsOfYKe4enISI1NVpTACq6HjQjMkLd1BcWu50HOOHjp4s5tZpy9mwJ8/jn+2JQhAHZFdaznGtq8k+NTkWABEZKyLpIpKem5t7XkFzTxSR1r4ZVyRHn9fxxpyJiHDXoET2HDvFrO+sVWA8b/qSnSzafoiwEM/f2vXEJ1b3q7XWcJ+aHFuxUnWKqqapalp09Pn9IB8/KIm3f93fWgOmTlyeHM0F8U2YtGAHpWXWKjCek3eqhFdd0+gmt4r0+Od7ohDkAG0rLccDe2u4T02O9ajgICsCpm6ICHcPSmL3kQI+XFOn/4xNgHl1yS5OFJUyfmDddHLxRCFYCSSJSAcRCQNuAj6uss/HwM9dvYf6AXmquq+GxxrjMwZ3iSE1NopJCzIoK6+2cWtMrVQMlZ/J0DqcOMvtQqCqpcB4YA6wGXhHVTeKyB0icodrt9lAJpABvAzcebZj3c1kjFNEhLsHJ7Lz0Ek+XWetAuO+177N4nhhKXcPqrsu7yGe+BBVnU3FD/vK616s9F6BcTU91hhfNiy1NSmtInl+fgbXXNCGILscac5T5aHyu8fX3cRZAfdksTF1LShIuGtwIhkH8/l8w36n4xgf9sbyiqHy76rjB2CtEBhTB0Z0i6VTdATPz99Oud0rMOfh9FD5lyW1pHcdD5VvhcCYOhAcJNw1KIkt+08wd9MBp+MYH/Tmit0cyi9mQj0Mh2OFwJg6cvUFsXRoGcFz87ZTcZvMmJopLCnjxa93cHGnFqQl1P1Q+VYIjKkjIcFBjBuYyKZ9x5m3+aDTcYwPqe+h8q0QGFOHru3ZhnbNG/FvaxWYGvp+qPwO9TdUvhUCY+pQSHAQ4wcmsn5PHgu3nt8YWSawvHN6qPw6fG6gKisExtSx63rHEd+sIf+yVoE5h6LSMiYvyPh+5rv6YoXAmDoW6rpXsDb7GF9vs1aBObP3VuWwN6+QCfU8VL4VAmPqwY97xxPXtKHdKzBnVFxazgsLKibOuiypZb2e2wqBMfUgLCSI31zRie92H2PR9kNOxzFe6L1VFRNn1XdrAKwQGFNvfpIWT5sm4fzrq23WKjD/o7i0nEkLMujRtimXOzBxlhUCY+pJg5Bg7hyYyGprFZgqPlhd0Rq4x6FpdK0QGFOPTrcK7F6BOa24tJz/LMigR3wTrkhxZhpdKwTG1KPTrYJVWUdZnGGtAgPvr84h5+gp7hma7Ng0ulYIjKlnp1sF//zS7hUEuuLScv4zP4OebZtyhQP3Bk5zqxCISHMR+VJEtru+/mCsVBFpKyILRGSziGwUkQmVtj0qIntEZI3rNdKdPMb4gsr3Cr6xewUB7XRPoXuGOHNv4DR3WwQTgXmqmgTMcy1XVQrcr6pdgH7AOBFJrbT9n6ra0/WymcpMQLgxrS1xTRtaqyCAne4p1KudMz2FKnO3EIwCZrjezwCurbqDqu5T1dWu9yeomJs4zs3zGuPTwkKCGD8okTXZx2wMogD17qpsV2vAuXsDp7lbCFqp6j6o+IEPxJxtZxFJAHoByyutHi8i60RkenWXliodO1ZE0kUkPTfX/uMY33dDn3jimzXkn/ZcQcApLCnjP/Mz6N2uKQPq+Sni6pyzEIjIVyKyoZrXqNqcSEQaA+8D96jqcdfqyUAnoCewD3jmTMer6hRVTVPVtOhoZ5tRxnhCaHAQdw9KYl1Ons1XEGBmrtjNvrxC7h+W4nhrAGpQCFR1iKp2q+b1EXBARGIBXF+r/dcsIqFUFIE3VPWDSp99QFXLVLUceBno64lvyhhfcV3vONq3aGStggByqriMSQt3cFGH5lzcqf5GGD0bdy8NfQyMcb0fA3xUdQepKHfTgM2q+myVbbGVFq8DNriZxxifcrpVsHHvceZs3O90HFMPXl+WRe6JIu5z8LmBqtwtBE8AQ0VkOzDUtYyItBGR0z2ALgFuBQZV0030KRFZLyLrgIHAvW7mMcbnXNsrjk7RETz75TbKyq1V4M9OFpXy4tc7uDSxJRfV0+xjNRHizsGqehgYXM36vcBI1/vFQLVlT1Vvdef8xviD4CDh3qHJjH/zOz5Zu5dre1mnOn8149tdHD5ZzL1Dk52O8j/syWJjvMDIbrF0bh3Jv77aRklZudNxTB3IO1XCS19nMjAlmj7tz9hB0hFWCIzxAkFBwv3DUth1uIAPVuc4HcfUgamLMsk7VcL9w1KcjvIDVgiM8RJDusTQo21TnpuXQVFpmdNxjAcdyi9i2uKdXNU9lm5xTZyO8wNWCIzxEiLCb4cls+fYKd5cvtvpOMaDJi/cQWFJmdfdGzjNCoExXuTSxJb079iC/8zPIL+o1Ok4xgP25Z3iv8uyuL53PIkxjZ2OUy0rBMZ4ERHhgeEpHD5ZzPTFO52OYzzguXkZqCoTBic5HeWMrBAY42V6t2vG0NRWvPxNJkdPFjsdx7hhR24+76Rnc3PfdrRt3sjpOGdkhcAYL/TbYSnkF5cy+esdTkcxbnhm7lYahAQxfpD3tgbACoExXimldSTX9YpjxtJd7D12yuk45jyszT7G7PX7+dVlHYmObOB0nLOyQmCMl7p3SDKq8M8vtzkdxdSSqvLkF1toHhHG7Zd1cDrOOVkhMMZLtW3eiFv7t+f91Tls3X/C6TimFhZtP8TSHYcZPzCRyPBQp+OckxUCY7zY+IGJRDQI4ckvtjgdxdRQeXlFayCuaUN+1q+d03FqxAqBMV6sWUQYv7miE/O3HGRZ5mGn45ga+HDNHjbuPc7vhqfQICTY6Tg1YoXAGC/3i0s60DoqnMc/32KT13i5wpIy/jFnK93jmnDNBW2cjlNjVgiM8XLhocHcNzSZtdnH+HTdPqfjmLOYvmQne/MKeXBkF4KCvGPSmZpwqxCISHMR+VJEtru+Vju2qojsck1As0ZE0mt7vDGB7sd94uncOpInv9hCYYkNSOeNDucXMXnBDoZ0iaG/l0xBWVPutggmAvNUNQmY51o+k4Gq2lNV087zeGMCVnCQ8PBVqeQcPcWrS3c5HcdU4/n5GRSUlDFxRGeno9Sau4VgFDDD9X4GcG09H29MwLg0qSWDOscwaX4Gh/OLnI5jKsk4eIL/Lsvipxe2JTEm0uk4teZuIWilqvsAXF9jzrCfAnNFZJWIjD2P440xwIMjO1NQUsa/vtrudBRTyd8+20wj170cX3TOOYtF5CugdTWbHqrFeS5R1b0iEgN8KSJbVPWbWhyPq4CMBWjXzjf65hrjaYkxkdzctx1vrtjNz/u3J6mV7/326W8Wbj3Igq25PDSyCy0be/dQEmdyzhaBqg5R1W7VvD4CDohILIDr68EzfMZe19eDwCygr2tTjY53HTtFVdNUNS06Oro236MxfuWeIUlEhAXzl083WXdSh5WWlfPYZ5tJaNGIMRcnOB3nvLl7aehjYIzr/Rjgo6o7iEiEiESefg8MAzbU9HhjzP9q0bgB9w5NZtH2Q3y1+Yy/O5l68OaK3WQczOfBkV0IC/Hd3vjuJn8CGCoi24GhrmVEpI2IzHbt0wpYLCJrgRXAZ6r6xdmON8ac3S392pMU05i/frrJupM65OjJYp79chsXd2rB0NRWTsdxyznvEZyNqh4GBlezfnpdfEUAAA6uSURBVC8w0vU+E+hRm+ONMWcXGhzEn67pyi3TljNt8U7GDUx0OlLAeXruVk4UlvKna7oi4jsPj1XHd9syxgS4S5NacmXXVkxakMH+vEKn4wSUdTnHeGvFbsb0TyClte/fsLdCYIwPe/iqVMrKlb/N3ux0lIBRXq488tFGWkQ04J6h3j3zWE1ZITDGh7Vt3ohxAxP5ZO1eFm8/5HScgPDe6hzWZB/jDyM6E+UDcw3UhBUCY3zc2AEdSWjRiEc+2kBRqd04rkvHCop58vMt9GnfjOt6xTkdx2OsEBjj48JDg/nLqG5kHjrJy99kOh3Hrz3x+RaOnSrhr6O6+dTooudihcAYPzAgOZqrusfy/PwMso8UOB3HL63cdYSZK7P51aUdSG0T5XQcj7JCYIyfePjqLoQECQ99uMGeOPaw4tJyHvxgPXFNGzJhiH/cIK7MCoExfiK2SUN+P6Iz32zL5cM1e5yO41deXpTJ9oP5/GVUVxqFufX4lVeyQmCMH7nlovb0bteUv3yyyYaq9pDM3Hyem7edkd1bM7iLbz9BfCZWCIzxI0FBwhM/voD8olL++ukmp+P4vPJy5ffvr6NBSBCPXtPV6Th1xgqBMX4muVUkd16RyIdr9rJgiw1K547/Lsti5a6jPHJNV2Kiwp2OU2esEBjjh+4c2ImkmMZM/GAdeQUlTsfxSdlHCnjyiy1cnhzNj3v7zzMD1bFCYIwfahASzLM39uRQfjF//mSj03F8Tnm5MvGDdQSJ8Pfru/v8oHLnYoXAGD/VPb4J4wYm8sF3e5izcb/TcXzKf5dlsSTjMH8Y2Zm4pg2djlPnrBAY48fGD0yka5soHpq13noR1VDGwRP8ffZmBqZEc3PfwJgW1wqBMX4sLCSIZ27swfFTpfzhg/X2oNk5FJeWc8/ba4hoEMKTN1zg95eETnOrEIhIcxH5UkS2u742q2afFBFZU+l1XETucW17VET2VNo20p08xpgf6tw6igeuTGHupgO8sXy303G82r/nbWPDnuM8fn13YiL9t5dQVe62CCYC81Q1CZjnWv4fqrpVVXuqak+gD1BAxQT2p/3z9HZVnV31eGOM+355aQcuS2rJXz/dxLYDJ5yO45WWZx5m8sId3JgWz5VdWzsdp165WwhGATNc72cA155j/8HADlXNcvO8xphaCAoSnrmxB5HhIdz91nc2z3EVh/KLuHvmdyS0iOARP35w7EzcLQStVHUfgOtrzDn2vwl4q8q68SKyTkSmV3dp6TQRGSsi6SKSnpub615qYwJQTGQ4T/+kB1v2n+Cxz+yp49PKy5V7317D0YIS/nNzbxo38L+xhM7lnIVARL4SkQ3VvEbV5kQiEgb8CHi30urJQCegJ7APeOZMx6vqFFVNU9W06Ojo2pzaGOMyMCWGXw/oyOvLdjPruxyn43iFyV/vYNH2Qzx6TVe/G166ps5Z+lR1yJm2icgBEYlV1X0iEguc7Xn2EcBqVT1Q6bO/fy8iLwOf1iy2MeZ8PXBlSsVUix+sp3PrKLrEBuYPP4ClOw7xzNytXNOjDaP7tnU6jmPcvTT0MTDG9X4M8NFZ9h1NlctCruJx2nXABjfzGGPOISQ4iOdv7kVUeCi/eX0VeacCcwiK7CMFjHtjNR2jG/P367oFTFfR6rhbCJ4AhorIdmCoaxkRaSMi3/cAEpFGru0fVDn+KRFZLyLrgIHAvW7mMcbUQExkOC/8rDc5R09x39trKCsPrOcLCopLuf21dErLlSm39iHSTyahP19u3RVR1cNU9ASqun4vMLLScgHQopr9bnXn/MaY85eW0Jw//agrf/xwA4/P3szDV6c6HaleqCoPvLuObQdOMP22C+kY3djpSI4LvNvjxpjv3dqvPTsO5jN18U46Rjfm5ov8f0iFf321nc/W72PiiM5ckXKujo6BwQqBMQHu4au6sOvwSR75aAPtWzTiksSWTkeqMzNX7Obf87ZzQ594fj2go9NxvIaNNWRMgAsJDuL50b3oFN2YO/67ig178pyOVCcWbDnIQx9uYEByNI8HwNDStWGFwBhDZHgor/7iQqIahvLz6SvIOJjvdCSPWpN9jDvfWE2X2Ehe+FlvQoPtR19l9qdhjAEgtklDXv/VRQQJ/HzacvYcO+V0JI9Yn5PHz6ctp2VkGNNvuzAgnxw+FysExpjvdWgZwYxf9OVEUSk/e3mZzxeDjXvzuGXaciLDQ3nr9n4BNaJobVghMMb8j65tmjDjF305nF/MjS9+y+7DBU5HOi+b9x3nlqnLaRQWzFu39yO+WSOnI3ktKwTGmB/o3a4Zb97ej5PFpfzkpaU+d89geeZhbnzpWxqEVBSBdi2sCJyNFQJjTLW6xzdh5th+lJUrN770LauyjjgdqUbmbNzPrdNXEB3ZgPd+05+ElhFOR/J6VgiMMWfUuXUU7/y6P1HhIYx+eTkfrdnjdKQzUlVmLN3Fb15fRWpsFO/dcbFdDqohKwTGmLPqGN2YWXdeQs+2TZkwcw3Pzt3qdWMTFZaUcf+7a/nTxxsZ1DmGN2+/iOYRYU7H8hlWCIwx59QsIozXf3kRN/SJ57n5GdwydTkHjhc6HQuA3YcLuP6Fpcz6bg/3Dklmyq1pNAqzLqK1YYXAGFMjYSFBPH3DBTz14wtYk32M4f/6hnmbD5z7wDqiqry+LIsR//6GnKMFTBuTxoQhSQQF2RPDtWWFwBhTYyLCjRe25ZO7LqV1k4b8ckY6495czf68+m0dZB8p4JZpy3n4ww30ateM2RMuY1DnVvWawZ+Iqndd66uJtLQ0TU9PdzqGMQGtsKSMl77O5IWFGYQECROGJPHz/gmEhwbX2TmPFRQzaUEGM5ZmERosPHRVKqP7trVxg2pIRFapatoP1lshMMa4Y/fhAh79ZCPztxykZeMG3H5ZB37Wr71Hh3I4lF/EW8t38/KiTE4UlXJD73juG5ZMbJOGHjtHIKiTQiAiPwEeBboAfVW12p/OIjIc+DcQDExV1dMzmTUH3gYSgF3Ajap69FzntUJgjHdRVZbvPMKkBRks2n6IqPAQru7Rhmt7xpHWvtl5XbcvKSsnfddRZq7czez1+ygpUwZ1juF3w1Po3Dpw51l2R10Vgi5AOfAS8NvqCoGIBAPbqJiqMgdYCYxW1U0i8hRwRFWfEJGJQDNV/f25zmuFwBjvtSb7GK8s2cncjQc4VVJGmybh9OvUgj7tm9GrbTPatWhERFjwDy7n5BWUsP3gCbYdyGfJjkN8sy2XE4WlRDYI4cd94rmlX3sSY2w2MXecqRC4O1XlZteHn223vkCGqma69p0JjAI2ub5e4dpvBrAQOGchMMZ4r55tm/Lvm3pxsqiULzcd4PMN+/hmWy4frP6/h9EahgYTHdkAgKLSMk4Vl3G8sPT77dGRDRjRrTWDOsdwWVI0ETZiaJ2qjz/dOCC70nIOcJHrfStV3QegqvtE5IzzxonIWGAsQLt2/j+dnjG+LqJBCNf2iuPaXnGoKruPFLAm+xj78wo5eKKIQ/lFBInQICSIBiFBxDVrSGJMYxKjI2nbvKHdAK5H5ywEIvIV0LqaTQ+p6kc1OEd1f5u1vh6lqlOAKVBxaai2xxtjnCMitG8RQfsWNu6PNzpnIVDVIW6eIwdoW2k5Htjren9ARGJdrYFY4KCb5zLGGFNL9fFA2UogSUQ6iEgYcBPwsWvbx8AY1/sxQE1aGMYYYzzIrUIgIteJSA7QH/hMROa41rcRkdkAqloKjAfmAJuBd1R1o+sjngCGish2KnoVPeFOHmOMMbVnD5QZY0yAOFP3URtryBhjApwVAmOMCXBWCIwxJsBZITDGmADnkzeLRSQXyDrPw1sChzwYxwm+/j1Yfuf5+vfg6/nBme+hvapGV13pk4XAHSKSXt1dc1/i69+D5Xeer38Pvp4fvOt7sEtDxhgT4KwQGGNMgAvEQjDF6QAe4Ovfg+V3nq9/D76eH7zoewi4ewTGGGP+VyC2CIwxxlRihcAYYwJcQBUCERkuIltFJMM1R7JPEZHpInJQRDY4neV8iEhbEVkgIptFZKOITHA6U22ISLiIrBCRta78f3Y60/kQkWAR+U5EPnU6y/kQkV0isl5E1oiIz40+KSJNReQ9Edni+r/Q3/FMgXKPQESCgW1UDHedQ8U8CaNVdZOjwWpBRAYA+cBrqtrN6Ty15Zp8KFZVV4tIJLAKuNZX/g6kYu7ECFXNF5FQYDEwQVWXORytVkTkPiANiFLVq53OU1sisgtIU1WffKBMRGYAi1R1qmuOlkaqeszJTIHUIugLZKhqpqoWAzOBUQ5nqhVV/QY44nSO86Wq+1R1tev9CSrmp4hzNlXNaYV812Ko6+VTv0mJSDxwFTDV6SyBSESigAHANABVLXa6CEBgFYI4ILvScg4+9EPI34hIAtALWO5sktpxXVZZQ8W0ql+qqk/lB/4F/A4odzqIGxSYKyKrRGSs02FqqSOQC7ziujw3VUQcn8g5kAqBVLPOp36b8xci0hh4H7hHVY87nac2VLVMVXtSMfd2XxHxmUt0InI1cFBVVzmdxU2XqGpvYAQwznXJ1FeEAL2ByaraCzgJOH6/MpAKQQ7QttJyPLDXoSwBy3Vt/X3gDVX9wOk858vVnF8IDHc4Sm1cAvzIdY19JjBIRF53NlLtqepe19eDwCwqLvv6ihwgp1JL8j0qCoOjAqkQrASSRKSD6wbNTcDHDmcKKK6brdOAzar6rNN5aktEokWkqet9Q2AIsMXZVDWnqn9Q1XhVTaDi3/98Vb3F4Vi1IiIRro4GuC6pDAN8phedqu4HskUkxbVqMOB4Z4kQpwPUF1UtFZHxwBwgGJiuqhsdjlUrIvIWcAXQUkRygD+p6jRnU9XKJcCtwHrXdXaAB1V1toOZaiMWmOHqgRYEvKOqPtkF04e1AmZV/E5BCPCmqn7hbKRauwt4w/ULaSbw/xzOEzjdR40xxlQvkC4NGWOMqYYVAmOMCXBWCIwxJsBZITDGmABnhcAYYwKcFQJjjAlwVgiMMSbA/X+pJ0Fp45JVoQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.plot(x, sin_x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "### Set the aspect ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The x and y on a sin curve should have equal aspect because they are in the same units. To reflect this in our visualization, we use the .set_aspect function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.plot(x, sin_x)\n",
    "_ = ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# What are the points being plotted?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "We can use the marker *kwarg* to put a marker at every x,y pair. You can find a listing of marker styles in the [marker reference](https://matplotlib.org/examples/lines_bars_and_markers/marker_reference.html) or make [custom markers](https://matplotlib.org/3.1.0/gallery/lines_bars_and_markers/marker_reference.html). We make the figure using the `figsize=(h,w)` kwarg so that we can see the markers. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "_ = ax.plot(x, sin_x, marker='*')\n",
    "_ = ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's change colors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "It's hard to see the markers and the lines, so we can change the colors of our marker or lines (or both). We are modifying the following parameters here:\n",
    "* `color` - changes the color of the line\n",
    "* `markerfacecolor` - changes the face color of the marker\n",
    "* `markeredgecolor` - changes the edge color of the marker "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "_ = ax.plot(x, sin_x, marker='*', markerfacecolor='white', markeredgecolor='blue', color='red')\n",
    "_ = ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's modify the size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.plot(x, sin_x, markersize=20, linewidth=20)\n",
    "_ = ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's change up the whole line by adding texture"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Sometimes we need to do vary the texture of the line. We can do this using the [linestyles parameter](https://matplotlib.org/gallery/lines_bars_and_markers/linestyles.html#sphx-glr-gallery-lines-bars-and-markers-linestyles-py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.plot(x, sin_x, markersize=20, linestyle='-.')\n",
    "_ = ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's digitally sample our sin curve"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Sometimes our data is sampled at step intervals and we want to reflect that in our line. We can do this using the [`drawstyle` parameter](https://matplotlib.org/api/_as_gen/matplotlib.lines.Line2D.html?highlight=drawstyle#matplotlib.lines.Line2D.set_drawstyle). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,5))\n",
    "_ = ax.plot(x, sin_x, drawstyle='steps')\n",
    "_ = ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's add a legend"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "We add a legend using the `label` parameter. Then we use `ax.legend` to display the legend. More information on customizing the legend position and appearance can be found in the [legend guide](https://matplotlib.org/3.1.0/tutorials/intermediate/legend_guide.html). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAACJCAYAAAAvz4PUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAZrklEQVR4nO3deXyU5bXA8d8RAlEIhiUiEDCooCK7KeClYlSgICpqvVxRW7W2lCqt1OKKtYta7PVWW7UugBsVK9YW5SqCQEHg3qoQBNlEI6BEkE3ZcmXNuX+cSRNoAkxmeeedOd/PJx/mnXmZ94zEM8/7LOcRVcU551z6OyboAJxzziWHJ3znnMsQnvCdcy5DeMJ3zrkM4QnfOecyRN2gAzicZs2aaUFBQdBhOOdcaBQXF29R1bzqXkvphF9QUMDChQuDDsM550JDRD6t6bW4dOmIyDMisklEltXwuojIIyJSIiIfiEj3eFzXOefc0YtXH/5zwIDDvD4QaBf5GQY8EafrOuecO0px6dJR1bkiUnCYUwYDE9SW9b4jIrki0kJVN8Tj+u4IVOGLL6CkBFavhs2b4ZvfhF697PlbboEbb7Tn1q6FJ5+EE0+E/Hxo3RratYMmTYL+FM65GCWrD78VsK7KcWnkuX9J+CIyDLsLoE2bNkkJLu2UlsLcubBwISxYAIsXw65dB59z772W8PfutfO2bLHnP/sMHnoI9u07+PyWLaFjRygstC+Gc86Bhg2T83mci7N9+/ZRWlrK7t27gw6l1rKzs8nPzycrK+uo/47Eq5ZOpIX/uqp2rOa1N4Axqjo/cjwLuE1Viw/3noWFheqDtkdh3z5L2C1awFdfQdOm1qo/9ljo1g26d4fTT4dTT4WTT7bWe8OGIFL9+6na+6xbZ18AH34Iy5bBBx/A0qVw4ADMmAF9+8Knn8LWrXadmt7PuRSzZs0acnJyaNq0KRLC31tVZevWrezcuZO2bdse9JqIFKtqYXV/L1kt/FKgdZXjfGB9kq6d/nr3ti6XadOgcWN49lno3Bk6dYK6tfgnFrH3a9IEunSBiy+ufK2sDN59F3r2tOOxY+G3v7VuosaN7U7CW/4uxe3evZuCgoJQJnsAEaFp06Zs3rw5qr+XrIQ/BRghIi8BPYHt3n9fS59/Dk8/DVOnwrx5kJUFo0bBccdVnnPttYm7foMGcP75lccjR9oXTuPGdnzRRbBjh40JDB1q5zuXgsKa7CvUJv54Tcv8M/AP4DQRKRWRG0RkuIgMj5wyFVgNlADjgBvjcd2MUlwM11wDBQXwi19YK3rTJnttyBBLtEHIy4MLL7THqnDFFbB/P/zgB9CqFfzsZzam4JwLXFwSvqoOVdUWqpqlqvmq+rSqPqmqT0ZeV1W9SVVPUdVOquod80dr7ly44AIbLJ0yBUaMgE8+gZkzLaGmEhGLb8kSu/sYOBD+8AcbN7jhBli1KugInUtZ3//+91mxYkVCr+G1dFLV//yPJfpzz4Xly+HBB20Q9eGHLYGmMhGbyfPnP9uX0w9/CC++CB06wPXXW3+/c+4g48ePp0OHDgm9hif8VFRebn3gy5dbgl+92vrpjz8+6Miid9JJ8OijNptn5Eib3VO/vr3mu625DFVWVsagQYPo0qULHTt2ZNKkSRQVFf2zlEzDhg0ZPXo0Xbp0oVevXmzcuDEu1/WEnyq2b4fbb4dt2+CYY+CVVyzRjxx58IBsWJ1wAvzud9bib9TI+vnPO8/uApwLWlHRkX/+678OPv+55+zxli3/eu4RTJs2jZYtW7JkyRKWLVvGgAEHFyooKyujV69eLFmyhD59+jBu3LiYPl4FT/ip4pNPbMHTrFl23K5deiT6Q1W07r/80r7YvLXvMlCnTp2YOXMmt99+O/PmzeP4Q+7e69Wrx0WRiRhnnXUWa9eujct1U7paZtorKYH//m/46U9tcdTatak3EJsoJ5xQ+eUGMGaMjVGMGQO5ucHF5TLTnDm1P79Zs6j/fvv27SkuLmbq1Knceeed9O/f/6DXs7Ky/jntsk6dOuzfvz+6+GrgLfwgHDhg3RudO8Ovf20rVSFzkn0FkcrVuTt32iKuDh3sS9C5NLZ+/XqOO+44rrnmGkaNGsWiRYuScl1P+Mn28cc2g2XUKCtNsHy5lULIdGPG2ArevDy45BKbzbN9e9BROZcQS5cupUePHnTt2pX777+fu+++OynXjVstnURIq1o6qjBunHXf1K8Pjz1mK1FDvtov7vbssbueBx6wO54JE45qEMy5aKxcuZIzzjgj6DBiVt3nOFwtHW/hJ8OWLTB4sM1H/7d/swJkV13lyb469evD/ffD//4vZGdbGYfRo/+1eqdzLmqe8BNt6VKrJDl9us3CmT498/rqa6NnT1i0CK67Dn7zG7j11qAjci70fJZOorVubaWJX30Vzjor6GjCpWFDeOYZGDDACrSBDXjXqRNsXC4tqGqoC6jVpjveW/iJsG0b3HGH9Ufn5trqUk/2tTdkiN0VHThghdruvTfoiFzIZWdns3Xr1lolzVRQUQ8/Ozs7qr/nLfxEmD/fum/69z+4lLCLzf790KaNbeDiXAzy8/MpLS2Nup58KqnY8SoaPksnnj791GrHgO0U5Vs0JtaUKdC2rW304pwDfJZO4pWXwy9/Ce3b2x6y4Mk+0fbts1r7Z58Nf/tb0NE4Fwrx2gBlgIisEpESEbmjmteLRGS7iCyO/NwTj+umhLIy62P+1a9sXr23NpMjKwvefts2Vv/2t23hVgrfrTqXCmLuwxeROsAfgX7Y3rULRGSKqh5ayX+eqga0LVOCbNhg+70uWmSV9G65xefWJ1PLllbD5Hvfg7vuss3Wx46tLMjmnDtIPAZtewAlqroaILJv7WAgsVu3BG3pUhg0yKo+vvbawRt9u+TJzoaJE+GMM+Cee2DNGpsC26RJ0JE5l3Li0aXTClhX5bg08tyhzhaRJSLypoicWdObicgwEVkoIgtTdgR9xgybF37ggG3l58k+WCLw859bbf1337XVzGvWBB2VcyknHgm/uj6MQztTFwEnqWoX4FHg1ZreTFXHqmqhqhbm5eXFIbw4mzjR5oIXFFhy6dYt6IhchSuvtL1+N22yzVX27Ak6IudSSjy6dEqB1lWO84H1VU9Q1R1VHk8VkcdFpJmqbonD9ZMrN9fm1r/8cji3HEx355xjdXhKSrwv37lDxKOFvwBoJyJtRaQecCUwpeoJInKiRNYwi0iPyHW3xuHayVFebkkErN9+2jRP9qns9NMhslsQEybAn/4UbDzOpYiYE76q7gdGANOBlcDLqrpcRIaLyPDIaVcAy0RkCfAIcKWm8oqvQz38sLUcly61Y5+JEw6q8OKLlvDLy4OOxrnA+Urbo1FWBn/9K3znO57sw2bPHti7F3Jy7N/xuOP839ClNV9pWxtffQXDh8OOHdCgAXz3u54owqh+fUv2X39tO4z96Ec2u8q5DOQJvzobN9ouS88+C8XFQUfj4iE722buPPUUXH21tfqdyzBeLfNQn31mLcHPP4c33rAk4cJPxDZSadwYbrvNunf+8hf7InAuQ3gLv6qSEttgfPNmm8/dt2/QEbl4u/VWeOIJ+zIfNAh27Qo6IueSxhN+hRUroE8f6+udPduqMLr0NHy4Tdd8+23bs2DbtqAjci4pPOEDLF4M555r0/jefhu6dg06Ipdo11xji+cWLrQ7uS+/DDoi5xLOE/6KFdZPf+yxMHcudOgQdEQuWS6/HCZPhmXL4L77go7GuYTzQduTT4YrroDRo60+jsssgwbZXV2XLkFH4lzCZW4L/7337DY+OxvGjfNkn8l69rTfg6++sgJsn38edETOJURmJvwdO2DgQBgxIuhIXCopKYFZs2wjFefSUGZ26TRqBJMm2fZ4zlX4xjesjn7Dhna8e7fP03dpJbNa+DNmwAsv2OO+feHEE4ONx6WeimT/4otw5pmwdm2g4TgXT5mT8N96y3ameugh2L8/6Ghcqmvf3sZ4ioo86bu0kRkJf/p0uOQSq5M+YwbUzcyeLBeFwkLrz9+xw9Zo+JaJLg2kf8KfPh0GD7ZNrmfNgqZNg47IhUX37vY7s2uXtfRXrw46IudiEpeELyIDRGSViJSIyB3VvC4i8kjk9Q9EpHs8rntE06ZVJvuZMz3Zu+h162a/O570XRqIOeGLSB3gj8BAoAMwVEQOXa46EGgX+RkGPBHrdY9o2jS49FJbOestexeLiqRfVmZJ/5NPgo7IuVqJRwu/B1CiqqtVdS/wEjD4kHMGAxPUvAPkikiLOFy7elWT/cyZ0KRJwi7lMkS3btZwKCuDCy/0gX+XOAnchTAeCb8VsK7KcWnkuWjPiZ86deCsszzZu/jq2tWS/uOP+8C/S4ytW+GCC6yoXwLE47e2un3/Dv2KOppz7ESRYVi3D23atKldRP362Tx735LQxVvVSqoTJ0KvXnDKKcHF49JHRbL/8MOEVW+NRwu/FGhd5TgfWF+LcwBQ1bGqWqiqhXl5ebWPypO9S6Rt22DkSNtFy7lYVU32U6bYPg0JEI8W/gKgnYi0BT4HrgSuOuScKcAIEXkJ6AlsV9UNcbi2c8HIzYX58+Gkk4KOxKWDzZutEZHAZA9xaOGr6n5gBDAdWAm8rKrLRWS4iAyPnDYVWA2UAOOAG2O9rnOBO+20yiqbl15qxdeci8auXTZIe/rpsGpVQpM9gGgCR4RjVVhYqAsTNHjhXNwsX26rcbOzYc4cOPXUoCNyYbB9O5xzjq0VuvfeuL2tiBSramF1r6X/SlvnEu3MM+Hvf4c9eyzxf/xx0BG5MMjJsX77oqKkXdITvnPx0LmzJf29ey3pr1oVdEQuVW3caIv3jjkGHn7Ykn6SeMJ3Ll46dYLZs21RVlGR7ZfsXFUbNtjvxkUXBbJ4zxO+c/HUsaP146vCeefZBunOgW2dWVQE69bBU08FsnjPE75z8dahg22MXreuJX2fveM++8y6+jZssAq+ffoEEoYnfOcS4bTTLOlffjnUdsW4Sw+rV1uC37LF9uPo3TuwUDzhO5cop55qt+716tnCmgULgo7IJdtHH1nLfudOG9Tv2TPQcDzhO5cMP/oRDBpk1TZdZli2zFr2e/ZYsu+enG1ADsdL/jmXDI8+alM1GzQIOhKXLK+8YpV758yxlbQpwFfaOpds48dD48bw7W8HHYlLhH37ICvLZmpt3gwnnJDUy/tKW+dSxYEDMGECDBkCzz8fdDQu3mbNstZ8SYlV7E1ysj8ST/jOJVOdOvDmm3D++XDddfCHPwQdkYunVq1sf4ScnKAjqZYnfOeSrUEDeP11m7I5ciTcc09Ct7VzSTB/fmXVy7fegubNg46oWp7wnQtC/fowaRLccINVShwxwrp7XLiowpgxVvXyhReCjuaIfJaOc0GpWxfGjbN9lx98EDZtgj/9ycosu9RXXg6jRlkBtKuvhiuvDDqiI/KE71yQROA//xNOPBF+9jMrqDV5ctBRuSPZs8fGYF56CW6+GR56yKpfpriYEr6INAEmAQXAWmCIqn5VzXlrgZ3AAWB/TVOGnMtYt9xiSb9Vq6AjcUeyfTtcdplVRv3tb+HWW0Ozh3asX0l3ALNUtR0wK3Jck/NUtasne+dqcNVVtgwf4PHH4YMPgo3H/avSUuuvnz/f+uxvuy00yR5iT/iDgYrJxM8Dl8b4fs65nTttIPCxx4KOxFW1ZAn06AGffgpTp1q/fcjE2offXFU3AKjqBhGpaZWBAm+JiAJPqerYmt5QRIYBwwDaeJVBl4lycuDdd6FpUzvesQMaNQo2Jge5uVb5dPx42/cghI7YwheRmSKyrJqfwVFcp7eqdgcGAjeJSI3FoFV1rKoWqmphXl5eFJdwLo20bGlTN7dvt1blzTcHskNSxlO1QfTycjjpJPjHP0Kb7OEoEr6q9lXVjtX8vAZsFJEWAJE/N9XwHusjf24CJgM94vcRnEtjDRrAwIHwyCNw8cWwbVvQEWWWGTNsgdykSXYcov766sTahz8FuDby+FrgtUNPEJEGIpJT8RjoD/i+b84djbp1bZ73k0/CzJnW2ve9chOvYhFcv34wZUoo5tgfjVgT/gNAPxH5GOgXOUZEWorI1Mg5zYH5IrIEeA94Q1WnxXhd5zLLD39oNdW3b7dNNF59NeiI0tf8+XDGGfbFKmJ3ViFv2VeIKeGr6lZVvUBV20X+/DLy/HpVvTDyeLWqdon8nKmq98cjcOcyzjnnQHGx1Wu57DK4807v148nVdu34Lzz7HEa1jdK/aVhzrlK+fkwbx4MGwYPPAB9+8Lu3UFHFX47dsDQofCTn9iYyYIFcOaZQUcVd15awbmwyc62vXJ794ZFi7z2TqwWLYL/+A9YswZ+8xu4/fZQlEmojfT8VM5lgu9+F37/e3u8eLF18ezdG2xMYVJebvsRnH223SXNmWP/DdM02YMnfOfSwxtv2E5aO3YEHUk4qNoWkyNHQv/+8P778M1vBh1VwnnCdy4djB5ttXeaNbM9VZ9/3lqw7mAVg7EicMkl1jU2ZYr9d8sAnvCdSxcVpRj+8hcr3VtUBB99FGREqWXnTpvdVLGX8PXX2+B3mky5PBqe8J1LN0OHwnPPWYu/c2e47z7v2wdbtfz11/B//xd0JIHxhO9cuhGBa6+FlSth8GD4+c+hWzer355p3n8fvvUt+OILG4ydNg1uvDHoqALjCd+5dNWihdWAef11KCuD88+HK66AtWuDjizxNm+Gm26CwkKbwVTRtZVB3TfV8YTvXLobNMha+/feC2++aSt1V60KOqrE+Ppr20vglFNsQPbGG+2z9qmxQG9G8YTvXCY49li4+25LfqNHQ/v29vzs2TaYGXa7d9uGMaeeCnfdZXczy5ZZqYTc3KCjSxme8J3LJPn51qcvYoXYLr7YNk8Ps7feshb9j39sCX/OHCsud/rpQUeWcry0gnOZ6vjjrYXfpIkdL15c2Q3SqVOwsR3JZ59ZCeO2baF5c0v0L7xgU1EzvJ/+cLyF71wm+8Y3rHUM8N57Np2zc2fr854wITW7e/buhS5d7E4F7PHbb1uVS0/2h+UJ3zlnhg2D0lJ48EFYv96mdjZvbvP6J0+GXbuSH9PevTbQfMMN9iWkCvXq2RfT/V5pPVoxJXwR+XcRWS4i5SJSeJjzBojIKhEpEZE7Yrmmcy6BmjaFUaPg449tI5DrrrM+8ssvt9eGD688NxGlG8rLbUbRY4/BpZdCXh5ceKGtHm7duvJLZ/Bg22PWRSXWFv4y4HJgbk0niEgd4I/YBuYdgKEi0iHG6zrnEknEyi8//rgtWpo92wZF27Wz1/fvt43WH3vMjvfsscHSTz45uvr8Bw7Y3cTXX9vxzJk2s6ZxY+jQwa61dKltLfj66zavfuJEyMlJyMfNFDEN2qrqSgA5fL9ZD6BEVVdHzn0JGAz4xpzOhUFWlg2GFhVVPldWBkOGVPb/r1hhfegVcnMtOefkWL3+AwfsS+K++6zl/s47Vp1y+nSrVqlqrferr7bFUkVFcPLJSfyQmSEZs3RaAeuqHJcCPWs6WUSGAcMA2rRpk9jInHO1c/zx8MgjlcennGKt9NJSWLcONm60BL5rl7Xi69a1L4769e38006DJ56onDrZr5/9uIQ6YsIXkZnAidW8NFpVXzuKa1TX/K9xs0hVHQuMBSgsLEy/TSWdS0eNGsEFFxz9+c2aHTwe4JLiiAlfVfvGeI1SoHWV43xgfYzv6ZxzLkrJmJa5AGgnIm1FpB5wJTAlCdd1zjlXRazTMi8TkVLgbOANEZkeeb6liEwFUNX9wAhgOrASeFlVl8cWtnPOuWiJaup2k4vIZuDTWv71ZsCWOIaTbGGPH8L/GcIeP4T/M3j80TtJVfOqeyGlE34sRGShqta4GCzVhT1+CP9nCHv8EP7P4PHHl5dWcM65DOEJ3znnMkQ6J/yxQQcQo7DHD+H/DGGPH8L/GTz+OErbPnznnHMHS+cWvnPOuSo84TvnXIZIu4Qf9tr7IvKMiGwSkWVBx1IbItJaRGaLyMrIXgk3Bx1TtEQkW0TeE5Elkc/wq6Bjqg0RqSMi74vI60HHUhsislZElorIYhFZGHQ80RKRXBF5RUQ+jPz/cHbgMaVTH36k9v5HQD+shs8CYKiqhqYUs4j0AXYBE1S1Y9DxREtEWgAtVHWRiOQAxcClIfs3EKCBqu4SkSxgPnCzqr4TcGhREZFbgEKgkapeFHQ80RKRtUChqoZy4ZWIPA/MU9XxkbIyx6nqtiBjSrcW/j9r76vqXqCi9n5oqOpc4Mug46gtVd2gqosij3di5TRaBRtVdNRU7OeXFfkJVctIRPKBQcD4oGPJRCLSCOgDPA2gqnuDTvaQfgm/utr7oUo26URECoBuwLvBRhK9SHfIYmATMENVw/YZfg/cBiRgH8KkUeAtESmO7JMRJicDm4FnI91q40WkQdBBpVvCj6r2vkscEWkI/BUYqao7go4nWqp6QFW7YuW8e4hIaLrXROQiYJOqFgcdS4x6q2p3bHvUmyLdnWFRF+gOPKGq3YAyIPAxxXRL+F57PwVE+r3/CkxU1b8FHU8sIrfhc4ABAYcSjd7AJZE+8JeA80XkhWBDip6qro/8uQmYjHXZhkUpUFrlzvAV7AsgUOmW8L32fsAiA55PAytV9aGg46kNEckTkdzI42OBvsCHwUZ19FT1TlXNV9UC7P+Bv6vqNQGHFRURaRAZ9CfSFdIfCM3MNVX9AlgnIqdFnrqAFNjHOxl72iaNqu4XkYra+3WAZ8JWe19E/gwUAc0iew38QlWfDjaqqPQGvgMsjfSBA9ylqlMDjClaLYDnI7O+jsH2cAjl1MYQaw5MtvYDdYEXVXVasCFF7cfAxEjjczVwfcDxpNe0TOecczVLty4d55xzNfCE75xzGcITvnPOZQhP+M45lyE84TvnXIbwhO+ccxnCE75zzmWI/wfRKGcmn0JYmQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.plot(x, sin_x, markersize=20, linestyle='-.', color='red', label='sin')\n",
    "_ = ax.set_aspect('equal')\n",
    "_ = ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Put it all together\n",
    "1. add a *cosine* plot to the axis (hint: ax.plot(x, ...)) is totally acceptable)\n",
    "3. make the *cosine* line bigger than the sin \n",
    "2. style the *cosine* as a dotted line (hint ':' is the short code for dotted)\n",
    "3. color the *cosine* line purple\n",
    "4. label the *cosine* and display the legend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# work through the practice"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's go back to our passenger records"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Let's do a little data cleaning using the `.dropna` method, which here drops any row containing a NaN. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"http://bit.ly/tcsv19\").dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "You can use `df.head()` to take a quick peak at the data.  This is helpful to remind ourselves what the column names and datatypes are!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pclass</th>\n",
       "      <th>survived</th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>ticket</th>\n",
       "      <th>fare</th>\n",
       "      <th>cabin</th>\n",
       "      <th>embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Allen, Miss. Elisabeth Walton</td>\n",
       "      <td>female</td>\n",
       "      <td>29.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>24160</td>\n",
       "      <td>211.3375</td>\n",
       "      <td>B5</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Allison, Master. Hudson Trevor</td>\n",
       "      <td>male</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Allison, Miss. Helen Loraine</td>\n",
       "      <td>female</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Allison, Mr. Hudson Joshua Creighton</td>\n",
       "      <td>male</td>\n",
       "      <td>30.00</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Allison, Mrs. Hudson J C (Bessie Waldo Daniels)</td>\n",
       "      <td>female</td>\n",
       "      <td>25.00</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>113781</td>\n",
       "      <td>151.5500</td>\n",
       "      <td>C22 C26</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pclass  survived                                             name     sex  \\\n",
       "0       1         1                    Allen, Miss. Elisabeth Walton  female   \n",
       "1       1         1                   Allison, Master. Hudson Trevor    male   \n",
       "2       1         0                     Allison, Miss. Helen Loraine  female   \n",
       "3       1         0             Allison, Mr. Hudson Joshua Creighton    male   \n",
       "4       1         0  Allison, Mrs. Hudson J C (Bessie Waldo Daniels)  female   \n",
       "\n",
       "     age  sibsp  parch  ticket      fare    cabin embarked  \n",
       "0  29.00      0      0   24160  211.3375       B5        S  \n",
       "1   0.92      1      2  113781  151.5500  C22 C26        S  \n",
       "2   2.00      1      2  113781  151.5500  C22 C26        S  \n",
       "3  30.00      1      2  113781  151.5500  C22 C26        S  \n",
       "4  25.00      1      2  113781  151.5500  C22 C26        S  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# First let's display some data using scatter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Here we are going to compare the age of the passengers to the fare they paid, because we want to see if there is a correlation. Traditionally scatter plots are used for these types of plots. Scatter takes the x and y plot\n",
    "Scatter can show 4 dimensions of data as users can encode variables as the x and y positions, size and color of the markers in one call of the function, and you can modify the shape via multiple calls to scatter. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "To start with, lets plot the passenger age against the fare paid:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nO3df5Af9X3f8ef7jgOfsMMJW1A4pEj2UFF+xGCuIEed1uDUIraDVWwn0lQZOkPKP3RiU48SqfXYMDVFLW2atAmd0sSJW1yMsLGQsScyFTideAz4FEkRslEgAYMkjOQE+RcHPp3e/eO73+V739uf3+/ud3fv+3rMaO5u9f3uvr/73d337uenuTsiIiIAI1UHICIi9aGkICIiISUFEREJKSmIiEhISUFEREKnVR1AP972trf5ypUrqw5DRKRR9uzZ8wN3Xxb1f41OCitXrmR6errqMEREGsXMvhf3fyo+EhGRkJKCiIiElBRERCSkpCAiIiElBRERCTW69ZFIv3bsPcJduw5x9MQM50+Mc81Fy3js6ePh35vXrWb9FZNVh9lY3ftX+7P+lBRkaO3Ye4StDx5gZnYOgCMnZrj38RfC/z9yYoatDx4A0IWsB1H7V/uz/lR8JEPrrl2HwgtWnJnZOe7adWhAES0uUftX+7P+lBRkaB09MVPo62S+uP2m/VlvSgoytM6fGC/0dTJf3H7T/qy3UpOCmT1vZgfMbJ+ZTQfLzjazR8zsmeDn0o7XbzWzZ83skJmtKzM2kc3rVjM+Npr4mvGxUTavWz2giBaXqP2r/Vl/g3hSuMbdL3f3qeDvLcBud78Q2B38jZldDGwALgGuA+42s+QzVqQP66+Y5M4bLmNyYhwDJifG2bRmxby/77zhMlWK9ihq/2p/1p+VOUezmT0PTLn7DzqWHQLe4+4vmdl5wDfcfbWZbQVw9zuD1+0CbnP3b8Wtf2pqyjUgnohIPma2p+NGfZ6ynxQc+LqZ7TGzm4Nl57r7SwDBz3OC5ZPAix3vPRwsm8fMbjazaTObPn78eImhi4gMn7L7Kax196Nmdg7wiJk9nfBai1i24DHG3e8B7oHWk0IxYYqICJT8pODuR4Ofx4AvA1cBLwfFRgQ/jwUvPwws73j7BcDRMuMTEZH5SksKZnammb2l/TvwPuApYCdwY/CyG4GHgt93AhvM7AwzWwVcCDxZVnwiIrJQmcVH5wJfNrP2dv6Pu/+pmX0b2G5mNwEvAB8FcPeDZrYd+A5wErjF3ZO7m4qISKFKSwru/jfAOyOW/y3w3pj33AHcUVZMIiKSTD2aRUQkpKQgIiIhJQUREQkpKYiISEhJQUREQkoKIiISUlIQEZGQkoKIiISUFEREJKSkICIiISUFEREJKSmIiEhISUFEREJKCiIiElJSEBGRkJKCiIiElBRERCSkpCAiIiElBRERCSkpiIhISElBRERCSgoiIhJSUhARkZCSgoiIhJQUREQkpKQgIiIhJQUREQkpKYiISEhJQUREQqUnBTMbNbO9ZvZw8PfZZvaImT0T/Fza8dqtZvasmR0ys3VlxyYiIvMN4knhY8B3O/7eAux29wuB3cHfmNnFwAbgEuA64G4zGx1AfCIiEig1KZjZBcAHgD/sWPwh4HPB758D1ncs/4K7v+7uzwHPAleVGZ+IiMxX9pPC7wK/BZzqWHauu78EEPw8J1g+CbzY8brDwTIRERmQ0pKCmX0QOObue7K+JWKZR6z3ZjObNrPp48eP9xWjiIjMV+aTwlrgejN7HvgCcK2Z3Qu8bGbnAQQ/jwWvPwws73j/BcDR7pW6+z3uPuXuU8uWLSsxfBGR4VNaUnD3re5+gbuvpFWB/Ki7bwJ2AjcGL7sReCj4fSewwczOMLNVwIXAk2XFJyIiC51WwTa3AdvN7CbgBeCjAO5+0My2A98BTgK3uPtcBfGJiAwtc19QbN8YU1NTPj09XXUYIiKNYmZ73H0q6v/Uo1lEREJKCiIiElJSEBGRkJKCiIiElBRERCSkpCAiIiElBRERCSkpiIhISElBRERCSgoiIhJSUhARkZCSgoiIhJQUREQkpKQgIiIhJQUREQkpKYiISEhJQUREQkoKIiISUlIQEZGQkoKIiISUFEREJKSkICIiISUFEREJKSmIiEhISUFEREJKCiIiElJSEBGRkJKCiIiElBRERCSkpCAiIqHSkoKZvcnMnjSz/WZ20MxuD5afbWaPmNkzwc+lHe/ZambPmtkhM1tXVmwiIhKtzCeF14Fr3f2dwOXAdWa2BtgC7Hb3C4Hdwd+Y2cXABuAS4DrgbjMbLTE+ERHpUlpS8JafBH+OBf8c+BDwuWD554D1we8fAr7g7q+7+3PAs8BVZcUnIiILlVqnYGajZrYPOAY84u5PAOe6+0sAwc9zgpdPAi92vP1wsKx7nTeb2bSZTR8/frzM8EVEhk6pScHd59z9cuAC4CozuzTh5Ra1ioh13uPuU+4+tWzZsqJCFRERBtT6yN1PAN+gVVfwspmdBxD8PBa87DCwvONtFwBHBxGfiIi0lNn6aJmZTQS/jwO/BDwN7ARuDF52I/BQ8PtOYIOZnWFmq4ALgSfLik9ERBY6rcR1nwd8LmhBNAJsd/eHzexbwHYzuwl4AfgogLsfNLPtwHeAk8At7j5XYnwiItLF3BcU2zfG1NSUT09PVx2GiEijmNked5+K+j/1aBYRkZCSgoiIhJQUREQklCkpWMsmM/tU8PcKM1NvYxGRRSbrk8LdwLuBjcHfPwb+oJSIRESkMlmbpF7t7u8ys70A7v6KmZ1eYlwyYDv2HuGuXYc4emKG8yfG2bxuNeuvWDDKSKb3TywZwx1+ODPb97p6eb80Rz/ftY6TcmRNCrNBfwOHVsc04FRpUUmkIk+C7ov4T147yeypVvPkIydm2PrgAYBw/Unb3rH3CFsfPMDMbKtbySuvzobbiVpXWlyd68r7/n419ULTxLijvuvND+zn9q8c5MSryTcUVR8ni1nW4qP/CnwZOMfM7gD+HPj3pUUlC7RPgiMnZnDeOAl27D3S97peeXU2TAhtM7Nz3LXrUKZt37XrUHhyRulcV5qodeV5fz+K3MeD1NS4o77r2VPOK6/Opn6OKo+TxS5TUnD3zwO/BdwJvASsd/cHygxM5ivyJEi7iLcdPTGTadvt12VZV6+vy/r+fjT1QtPUuLN8p3Gfo8rjZLFLLT4ysxHgL939UlpjF0kFijwJsr7n/InxTNs+f2KcIynrbK8ryzaj1pX1/f1o6oWmqXFnOW4g+nNUeZwsdqlPCu5+CthvZisGEI/EiDvYezkJsrxnfGyUzetWZ9r25nWrGR+LnySvc11potaV5/39KHIfD1JT4047btqiPkeVx8lil7VO4TzgoJntNrOd7X9lBibzFXkSRK1rbNSYGB/DgMmJce684bKwwi5t2+uvmOTOGy5jcmIcA848fTScHGPUjA9fOZlY+bdj7xHWbnuUVVu+yl27DvHhKyfDdXXHUqamXmjS4u7cv2u3PVqbuobu42ZifIyx0fnTqsTt/+73DvI4WewyDYhnZv8karm7/1nhEeUwbAPildX6KMu6sr6+u1UItE7suBM27+vL1sRWPBAfd932b5qm7v+mSRoQT6OkSqHWbns0sqx3cmKcb265tu/XSz7avxKl71FSzWyNmX3bzH5iZj8zszkz+1GxYcpikLfSs6mVpE2h/St5Za1T+H1aQ1w8A4wDvxEsE5knb6VnUytJm0L7V/LKPEqquz8LjLr7nLv/MfCe0qKSxspbWdvUyt2m0P6VvLIOc/FqMNbRPjP7j7Q6sJ1ZXljSVO1KwayVhXlfL/lo/0peWVsf/TzwMnA6cCtwFnB38PRQGVU0i4jkl1TRnPikYGYr3P0Fd/9esOg14PaiA5TBU9O//Oq0z+oUiywuaXUKO9q/mNmXSo5FBqSpA6hVqU77rE6xyOKTVqfQ2b3w7WUGIoOTNIBaHe8263BXXKd9VqdYBqnIOT/0dBUvLSl4zO/SYE1qu16XcfPrtM/qFMug9Hsc1OU4aoK04qN3mtmPzOzHwC8Ev//IzH6szmvN1aS263UZFrpO+6xOsQxKv8dBXY6jJkhMCu4+6u4/5+5vcffTgt/bf//coIKUYjWp7Xpd7orrtM/qFMug9Hsc1OU4aoKs/RSkAbKWmdat7XpS3L2Om59nAL8q9lk/5dt5Y/nkjgPc98SLzLkzasbGq5fzmfWX9RR3VfqdP0HzL2SnAfEWiaaNhtmWFvcndxzg3sdfWPC+TWtWxF7Ysu6LqvbZILfby/6ro373WVPPj7L0PSCe1F9Ty0zT4n7s6eOR74tbnmWdeV9XtEFu974nXsy1vK76nT9B8y9kp+KjRaKpZaZpcffyubK+p6p9NsjtzsWUBMQtr7P1VyRP1lT2+4eFnhQWiaa2SEmLu5fPlfU9Ve2zQW531CzXcpHSkoKZLTezx8zsu2Z20Mw+Fiw/28weMbNngp9LO96z1cyeNbNDZraurNgWo6a2SEmLu5fPlfU9Ve2zQW5349XLcy0XKbP46CTwCXf/CzN7C7DHzB4B/gWw2923mdkWYAvw22Z2MbABuAQ4H/i/Zvb33X0uZv3SoW4tirJKi7uXz5X1PVXts0Fut12Z3PTWRzI4A2t9ZGYP0ZqY5/eB97j7S2Z2HvANd19tZlsB3P3O4PW7gNvc/Vtx61TrIxGR/CpvfWRmK4ErgCeAc939JYDg5znByyaBziYRh4Nl3eu62cymzWz6+PH4FigiIpJf6UnBzN4MfAn4uLsnDY0RVfO14DHG3e9x9yl3n1q2bFlRYYqICCUnBTMbo5UQPu/uDwaLXw6KjQh+HguWHwY6a78uAI6WGZ+IiMxXZusjA/4I+K67/07Hf+0Ebgx+vxF4qGP5BjM7w8xWARcCT5YVn4iILFRm66O1wK8DB8xsX7Ds3wDbgO1mdhPwAvBRAHc/aGbbge/Qarl0i1oeiYgMVmlJwd3/nOh6AoD3xrznDuCOsmISEZFk6tEsIiIhJQUREQkpKYiISEhJQUREQho6Wxqle8ayay5axmNPH2/UeE8idaakII3RPXvWkRMz82YVO3Jihq0PHgBQYhDpkYqPpDGiZizr1oTZ5kTqTElBGiPrzGR1n21OpM6UFKQxss5MVvfZ5kTqbCjrFFRZOVjd+7vX/bt53Wo2f3E/s3Pxc4CUOXNa2uco6nMuJtonzTN0SUGVlYMVtb/72r9d+WAEOGvJGCdenS31opP2OQr/nIuA9kkzDV1SyFNZqQO3f1H7u9f9e9euQ8yemp8VTgFLTj+NvZ96X7+hpm476XMU+TmbrPPJYMSMua6ZHYdxnzTN0CUFVVYOVtx+7GX/FrmuorddZWx10f1k0J0Q2o4M0T5poqGraFZl5WDF7cde9m+R6yp621XGVhdZnsIBRi1u8GSpg6FLCpvXrWZ8bDTxNWVWVg6bqP3d6/4tcl1Fb7vK2Ooi61NR3BOE1MPQFR+1yzLV+mgw4vb3XbsOcev9+3Lt/6h1Deq7Stt2lbHVxfkT45mKhiaH6OmpicwbnLWnpqZ8enq60hjU5C6f7nLnKONjo9x5w2WZ9mO/+7/I5sllrqtOx1VcbEV/t1IeM9vj7lOR/6ek0Luok0AHfbK12x7NfDf5zS3XJr6m3/1f5EWs7HXV5bhKi019gJohKSkMXfFRkdQMMb8iW3/1u/+LbJ5c9rrqclylxdb+J801dBXNRVIzxPyKbP3V7/4v8nWDWFcdjqs6xybFUFLog5oh5ldk669+93+RrxvEuupwXNU5NimGkkIf1Awxv/VXTHLnDZcxOTGO0ao72LRmxby/s5ad97v/i0xQZa+rLsdVnWOTYqhOoQ9FN0PM2+Kkzi1UkhRV7tzv/o96/5LTR3jm2E/D17xrxVmZ1ldkU+c6N2+tc2xSDLU+qom8LU7q3EKlqT6548C8wRHbNq1ZwWfWX1ZBRCLlSGp9pOKjmkhq1VHE68u2Y+8R1m57lFVbvsrabY+yY++Rxm33videzLVc0lV1XEjvVHxUE3lbdeRdXmZRU1VDJBe93bjhF+KW17n4rg6xaejsZtKTQk3kbdWRZ/mOvUfY/MX9HDkxg9M6OT/xwH4uv/3rhdzBVfXUUvR24wZqi1oetU83f3F/Le6E2xfjzti2Pnhg4LHV7WlWslFSqIm8rTryvP72rxxcMFvZ3CnnxMxsIReNqtquF73djVcvz7w8ap/Ozjm3f+VgT9vuV2cxzSe274+8GH/8/n0DLcJRn4ZmUlKoiaimmkmVxnle/8qrs6nb7+cOrqq260Vv9zPrL2PTmhXhk8GoWWwlc9w+zbKvi9b9ZJA0CukgnxrUp6GZSqtTMLPPAh8Ejrn7pcGys4H7gZXA88Cvuvsrwf9tBW4C5oDfdPddZcVWV3mbahY9pECvd3Cb162ObAlVdtv1Mrb7mfWXNa6lUdZ5DNoGNWRGVceF9KfMJ4U/Aa7rWrYF2O3uFwK7g78xs4uBDcAlwXvuNrPknkCS2cT4WKbX9XoHl/cppyhVbRfi92nWfV2kImexK1KV34/0rrQnBXf/f2a2smvxh4D3BL9/DvgG8NvB8i+4++vAc2b2LHAV8K2y4hsmt11/CZsf2L9gfuNO/d7BVTUQWlXbjdqnYyPGbddfMvBY4uYxGI2YI7nzPYOgAfKaZ9BNUs9195cA3P0lMzsnWD4JPN7xusPBsgXM7GbgZoAVK1aUGOriMYiJhQbVBLIOTS2hXj1744pp7ryhVQyWVoQzLD3pJZu69FOIagsYeYvj7vcA90CrR3OZQS0maXds7dYrvU4Ik9QevaiLSC/t3tO2nfT/WeYGSJvzIc9nK3K4ju73J33GPPtUfQ8Wv0EnhZfN7LzgKeE84Fiw/DDQ2e7vAuDogGMbWv2e6Gnt0Yu6iOSdZyBLsor7/6i4O4fAKPJiWMSFtjvpZ03yefdpned6kGIMuknqTuDG4PcbgYc6lm8wszPMbBVwIfDkgGNbdLIOMdBvJ6Ok9uhFdmDK2+49bdtJ/59n0px+Fd3JK0/ntbJ70kvzlNkk9T5alcpvM7PDwKeBbcB2M7sJeAH4KIC7HzSz7cB3gJPALe6evY1diZpafprn7rPfEz2uorN9Qepn3Z0mloxF9gOYWBLd4idu2+3lRVzgjpyYYdWWr/Z1bMRtr9d157mbj/vuRszCbXcWm43EVF53vn5Q50hTz826K7P10caY/3pvzOvvAO4oK55eNLn8NO3C0HlCxZ3oWVuorHxr9IUlSS+tX+L6ZMUtj2t90+6cFpdksPh1Rm6fYJiLB/YD+Y+NuAvzvHV/cT+37TzID2dmU+tG4kKPSj6b162ObJnW3m/dxWZp40PlPUd6vbA3+dysezKrS0VzLTW5/DTpLrj7hIo60btbqHxyxwHue+JF5twZNWPj1cvDTl6P/80ruWLrtfXLD2eiewt3Ls9ycWx/3rxJJs3sKee2nQdzHxtRrYcWrHuuNSwJRNeNpDU5hjcScec+Omt8LLEHdJxRM065R95QZD1H2uNHtYcLaSe/9ueKen3SjUwTzs0mJDMNc5GgyeWnSUMMxJWXj5pFdjJqzzPQPgnn3Ln38Rf45I4D4d9ZRK07T/l32rAJ3euKMxm8Pi7JZPkccU70sM7uTl5ZdNY53LbzYGpCALjmomUL9tGJmVkyvHWBOXee2/YBTsV891nOkTzjR2UdyqPu52YTBglUUkjQ5LFbkgbMiztxTgUn+je3XDvvriVtnoG40UW7Ra07z0mSNghglsrhztf38j1m/ax5rb9ikm9uuZbntn0gTFpp2kVOWRPRY08fzz0kRpp+zpE840dljfusCnqU59GEG00lhQRNno82aYiBvCdyWjly3OiincbHog+1PCdJ2rAJSSdW1OuzzKvcbc498SnkzNP7H50la1x5E9TREzOFX3wGdY5kjbuonF3W5EBNuNFUnUKCOvVa7UVch7W8A5UlDZfQbnGy9h1n8/jfvBL7unetmIhcHlfJ2nmSZK1ziFvX5MR4ZCez7u836WKftA86jY32f5+VNa52PEvjKsy7tPdplkYB7Wtr3LbbCWlQ50hSZXynEwWMUltmuX8TBglUUkixGMduyXsib7x6eeTcxfBG65hjP36Nt7zptNiijLjK6LSTJM8J2ssJ1/n9vmPr12JbK8WVnXfrtZ4iSVxCahczffpXLplXYRulcz+kVWqPjRh3ffSdrL9iMnbe6s6nw17PkbhktjSiiXGWyngo5o67zAYmTbjRVFIYUnlO5HYro3broyidrWOixL0v7STJc4L2e8IlFZNNZrxTLeKilKV12OiI8dPXT4ZPar/2D5fPG4IjbWyrrONgdX/33S3P+hGVzMZGjU//ysJBBbu/27PGx/jpz04ueG/nPim630hRRW91v9E077X9XQ1MTU359PR01WE0Uj9tpVdu+Wru7Y2a8dd3vj/3+1Zt+WpkEYbRqrgu0tptj8YWP2W5U20PQtfvCR8XR5Kitj1o/RyHne+dWDLGT147Oa8VVq/7JOk4KGqsq6qZ2R53n4r6Pz0pLGLdJ417q3ij+y4rb5lp1vL1TmvevjT/ByC5t/Q7tn6NNW9fyvN/O9Pzo3j3PhobsQUXlu4nl/a2Vr51PKxHGTXjw1f2fgeYpX9Fku6np+6+CGat8va6FVf0c9fc+d612x5dUBTVa5FPE8r9y6QnhUWquwgii3bZedqFo5cnhc5tdBc/pI1UmudzdN8dpq27u/hidMR4yxmnhckz7mIaFVeeO9O0u9xetJ+e0vZZ3jvouvfAheKfKJvwmfuhJ4Uh1Et79KxDFWRt7RK3jXbF5WfWX7agN273cBGdd+hZilS6h/JIqqSO6jw1d8oxg//ya5cn9rbNUtcRN/T2kRMzGG+07ClqXmcnW8JOu4Pufsr48esnmTsVvR/yKutim6UVWx51L/cvk/opLFL9Vool9bKMe7jM00S83fEtqjdue7iItnbHrqzaF4e0jnFJnafSetumVUZG9dS+9/EXwtiqfj6Piz+qx/Nc9/cz59y6fV/uNvx5eq/n1eQ+RXWjpLBIFdEKJu7CEdfKyIFNa7LNhtd+KolbV9TyXjpr5VneKa23bVonpKJ7DsMbw5AUIS7+rHG7k/vCXuYQD2kdGyU7JYVFqpfeut3iLhxxF+dRMx57+nimdfcyXESWntOd0i7cEzFDIsQt75R2Z1rGsAXtYUj6lXQH3UvcWS/sg2jq2R4qpHs4FclOSWGR6r5zWrpkjInxMYzWRW9sNPminHThSGrPn/UEb1/gozoqxS3/zPrL2LRmRWpCaf9/2oX7tusvYWxk/rpGSB4qoZ0w0u5M8z6pjY1a+P3Efb72OvMk1Pb3vXTJWKY76F6fMLN8700Y4kGGtKI5T2VXla0Qitz2ktNPyz3/cNy24jpytXvYJlUId7c+ytOBCVqJof3etN62aZ3ZojpE/ei12diio7ER47br34grqTIyaw9ceKMfRFrLpnYyS+ph3mnTmhWRncySpurME3enLBf2YW/q2RRD1yQ1T1PCfpsd9qOIJo9lxZ60blg4jELadvtJUEnzPOR1+e1fj63j6L5wZ5FlIqO4DlFJn2vH3iP86+37Eoe8HjH4nV+9vKdjOun7iGo+OzZivPlNp2XqB7HYm3o2RVKT1KFLCnl6K1bZs7HfbZcde1r7/356qVaViJOacz7fZ1l+nnb0afsga4/nso7p7iar3cNN9PN9FZnki7TYkpn6KXTIU9lV5djn/W477/vzHvRJRSdpbbyTthXXQuUT2/dz6/37KrsTXbvt0cQpMKOecLLMbRxV7JLWByLrEBh5jule54P+8WsnE2dAy/N9dBcHdvdpqUrdZksrO0ENXVLI08ml6A4xefS77TzvH+RBn7atuItWZ8e6W+/fx8fv38dkStFGlrmNO515+ig//Vl0WXrUFJjdn6PzgpZlbmMLXrd226PzPkfcs/uRE62pVLMOMxI1/WZccoJs80FnGayvM9Y8x1XSZE5VJoU6Tcs7iHN16IqPoh7Nu8tE43qewuKsUxhkMVnatnoZDC6PpPJzSO9UNqg444yPjWauBO6n53n3NvMWXY2a8ffOelOu4yqp+M4gtZgyT11UHoMclDFNUeeqio86xA3B2z55uu/wHMLE0EtlY1Fx5j3I87w/7iQv46KXVqx1zUXLMrWs6VXSMBhZtOOsavrEmdk5RoxM8yoXNXxGL0VXc+65j6ukJ6DOjnJtaU9qRd1BV1li0G0QRdpDlxRg4eiKaXPcthPCoIfN7Xf8lazvjzsZy5iPOO0Ey9r5rR/tE6iXXsftOLPOBFaGPsfN60l7n2UtupqcGOf7P3wt13GVpaltZ0e5tO+uqCKeOjWlHUSCGsrOa53zr2Y9sdtlv0XN1VonaXMw55U0v20VPYG7tU+gvNvqjLOIHuNN0t5nWY6J9n7Ke1xl7ZyYZ67pIo6nOg2hMYgxnobuSaGXIoO2qlsdlCWtM1oeaRVhacVa/d6Bj40aZ57eGvo6buKV9gmUZ1ujZvMuBFGfI6n1UVE39+Njo5xx2kjq021e7WHT0/ZZ3LESNex63Mi2ScdVZ+fEuPLzPHNNF3UHXZdRU/stVs5i6JJCvwOVpQ2P3LT2yzv2HuHVn51csHxsxHj1Z9mnNmzvh6gTNe0xfvp7f5c40Q20Kk0/8Avncf+3X5zXJn7E4KzxsQUdp9rxvPLqbFjk0W6tdNeuQ9x6/77YbXUbHTH+czBncac8F4q43tfAglZUUW3/2/ug3dO71xubKHnmoIgrSom6c+632CXt/VlmwluMvaXLTlBDlxTSHidHzcLZvOLuRLqHR65L++W84p6axsdGOHnK51W+d3+utA5M3Y4k7LPOi+Urr84yOtIaB6jdJLI9w9m9j7/AiLXie232VGyyimo2OT42yjUXLeP+J18Mk8Arr84yYoTbetPYCDOzpxbEvmbV0r6/z7xzHWe52UiaBa5zRrrOWfeytNJJ64PSve2kFkEfvnKy5xZBWe6KB9H6aNgMXZPULE3q2nc+SY+/Sc0SmzKXa95mle3P1U8RXFZLl4yx91Pvi73DThrX5xPb90f3C7DouSAmxsfY9+n38Rra84AAAAhESURBVI6tX4utGO1lfumo2Jr8VJmmyt7okk9Sk9Shq2jOUkHYLu7otVK0quaKeeWNs59WO3m1n1KSOjR1a1+UYps1xtz/tMvni65wj4qtjAlm6qLM+RJkcIYuKXS3JIhz9MRMz8MjN2Uo4Lxx9tpqpx95LtT9JqukeSL6NQwXzKbfJElL7eoUzOw64PeAUeAP3X1b0dvo7qeQ1MIh7/DITarcyjNMcq+tdnrVnrcgTx+KXi8+7bkb4trJx03uk6dH7aAvmFUUVdWpk5f0rlZPCmY2CvwB8MvAxcBGM7u4zG320+63Tu2Xe9GOP+kOOepzRe2zsRELJ3LpnNAnSXsCmK55bubNWxB3QY5a3svFp3Puhu528qNmiXUXcXMwRxUPDfKpsqqiKs2TvDjUqqLZzN4N3Obu64K/twK4+51Rr++lojnKYq8ATNNLBWHWffbP/+e3+OZf/92C5WvfcTaf/5fvzrSurMMpZ60Aj2pTn1fe4asHWQlbZQOIYT+XmqIx8ymY2UeA69z9N4K/fx242t3/VcdrbgZuBlixYsWV3/ve9yqJdbEp82TuTgydCaFonZ8jriNWERfiuEHSunUOmjaoC2adBnCTemrSgHhRJQ7zjm93vwe4B1pPCoMIahiU2SGmrAQQpftzlHUhzlqv0lk8NKhesSrbl37ULSkcBjoLiy8AjlYUiywCZV2Is1TSV1We3vQGEFKtWlU0A98GLjSzVWZ2OrAB2FlxTCILRDUy2LRmRS0aHTS9AYRUq1Z1CgBm9n7gd2k1Sf2su98R99qiKppFRIZJk+oUcPevAV+rOg4RkWFUt+IjERGpkJKCiIiElBRERCSkpCAiIqHatT7Kw8yOA3m6NL8N+EFJ4fSrrrEprvzqGltd44L6xlbXuKC/2H7e3ZdF/Uejk0JeZjYd1wyranWNTXHlV9fY6hoX1De2usYF5cWm4iMREQkpKYiISGjYksI9VQeQoK6xKa786hpbXeOC+sZW17igpNiGqk5BRESSDduTgoiIJFBSEBGR0FAkBTO7zswOmdmzZral4lg+a2bHzOypjmVnm9kjZvZM8HNpBXEtN7PHzOy7ZnbQzD5Wo9jeZGZPmtn+ILbb6xJbEMeome01s4drFtfzZnbAzPaZ2XRdYjOzCTP7opk9HRxv765JXKuDfdX+9yMz+3hNYrs1OPafMrP7gnOilLgWfVIws1HgD4BfBi4GNprZxRWG9CfAdV3LtgC73f1CYHfw96CdBD7h7v8AWAPcEuynOsT2OnCtu78TuBy4zszW1CQ2gI8B3+34uy5xAVzj7pd3tGevQ2y/B/ypu18EvJPWvqs8Lnc/FOyry4ErgVeBL1cdm5lNAr8JTLn7pbSmFdhQWlzuvqj/Ae8GdnX8vRXYWnFMK4GnOv4+BJwX/H4ecKgG++0h4J/WLTZgCfAXwNV1iI3W7IC7gWuBh+v0fQLPA2/rWlZpbMDPAc8RNHKpS1wRcb4P+GYdYgMmgReBs2lNd/BwEF8pcS36JwXe2KFth4NldXKuu78EEPw8p8pgzGwlcAXwBDWJLSii2QccAx5x97rE9rvAbwGnOpbVIS5ozW/+dTPbY2Y31yS2twPHgT8Oitz+0MzOrEFc3TYA9wW/Vxqbux8B/hPwAvAS8EN3/3pZcQ1DUrCIZWqHG8PM3gx8Cfi4u/+o6nja3H3OW4/1FwBXmdmlVcdkZh8Ejrn7nqpjibHW3d9Fq+j0FjP7x1UHROtO913Af3f3K4CfUm3x2gLBVMDXAw9UHQtAUFfwIWAVcD5wppltKmt7w5AUDgPLO/6+ADhaUSxxXjaz8wCCn8eqCMLMxmglhM+7+4N1iq3N3U8A36BVL1N1bGuB683seeALwLVmdm8N4gLA3Y8GP4/RKhu/qgaxHQYOB096AF+klSSqjqvTLwN/4e4vB39XHdsvAc+5+3F3nwUeBH6xrLiGISl8G7jQzFYFdwAbgJ0Vx9RtJ3Bj8PuNtMrzB8rMDPgj4Lvu/js1i22ZmU0Ev4/TOkmerjo2d9/q7he4+0pax9Wj7r6p6rgAzOxMM3tL+3daZdBPVR2bu38feNHMVgeL3gt8p+q4umzkjaIjqD62F4A1ZrYkOE/fS6tyvpy4qqzMGWBFzfuBvwL+Gvi3FcdyH61ywVlad003AW+lVVn5TPDz7Ari+ke0itX+EtgX/Ht/TWL7BWBvENtTwKeC5ZXH1hHje3ijornyuGiV3e8P/h1sH/c1ie1yYDr4PncAS+sQVxDbEuBvgbM6llUeG3A7rRuhp4D/DZxRVlwa5kJERELDUHwkIiIZKSmIiEhISUFEREJKCiIiElJSEBGRkJKCSI/M7J+ZmZvZRVXHIlIUJQWR3m0E/pxWxzWRRUFJQaQHwRhRa2l1PtwQLBsxs7uDce8fNrOvmdlHgv+70sz+LBicbld7eAKRulFSEOnNelpzAvwV8Hdm9i7gBlrDol8G/AatYdvbY0r9N+Aj7n4l8FngjiqCFklzWtUBiDTURlrDZkNrMLyNwBjwgLufAr5vZo8F/78auBR4pDV0DaO0hjoRqR0lBZGczOyttCbVudTMnNZF3mmNRBr5FuCgu797QCGK9EzFRyL5fQT4X+7+8+6+0t2X05pN7AfAh4O6hXNpDZIHrRmylplZWJxkZpdUEbhIGiUFkfw2svCp4Eu0JkA5TGsky/9Ba+a6H7r7z2glkv9gZvtpjUD7i4MLVyQ7jZIqUiAze7O7/yQoYnqS1uxn3686LpGsVKcgUqyHgwmBTgf+nRKCNI2eFEREJKQ6BRERCSkpiIhISElBRERCSgoiIhJSUhARkdD/B/wdaZdAj2jRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter(df['age'], df['fare'])\n",
    "_ = ax.set_xlabel('Age')\n",
    "_ = ax.set_ylabel('Fare')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Simplify code using the data kwarg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The `data` kwarg takes in any labeled data (dictionary, dataframe, record array, etc) and unpacks it for you based on the labels passed in as x, y, etc, kwargs. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Label all the things using set"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Setting each label individually using the .set_ methods can get tedious, so there's a meta-set function you can use to set all the labels in one shot. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', data=df)\n",
    "_ = ax.set(xlabel='age', ylabel='fare', title='Titanic Passengers')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's change the color"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "While that blue is lovely, sometimes we might want our dots to be a different color. Here we will use the color *kwarg* to change the color of our dots to hotpink. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', color='hotpink', data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's encode data using color"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Is there a difference in age and fare between people who survived and people who didn't? Here we will color the dots based on the survived column (remember 0 is dead and 1 is alive) using the `c` keyword arg. . The colors are yellow and purple because they are from the default [matplotlib colormap](https://matplotlib.org/examples/color/colormaps_reference.html) Viridis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', c='survived', data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Lets customize those colors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The viridis colormap is designed for quantitative datasets and survived is categorical. Instead of using the default, let's use a categorical colormap to make things prettier. You can find a full list of colormaps at the [colormap reference ](https://matplotlib.org/3.1.0/tutorials/colors/colormaps.html). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEGCAYAAACKB4k+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAgAElEQVR4nOzdd5xcVd348c/3Tp/tvWU3m04KBEIIvQgioAgIoiBNRVFAn0fRH00fH9QHQXz0QUVBlCoiBgtFbHQklDRqymY3bXezve9On3vP74+ZTHZ3ZluS2d2Q884rr9m5M3PnTLvfc8/5nnNEKYWmaZqmARhTXQBN0zRt+tBBQdM0TUvQQUHTNE1L0EFB0zRNS9BBQdM0TUuwT3UB9kVhYaGqrq6e6mJomqYdUNatW9ehlCpKddsBHRSqq6tZu3btVBdD0zTtgCIiO0e6TTcfaZqmaQk6KGiapmkJOihomqZpCTooaJqmaQk6KGgHtYGoyZs9A2zzhwDoCEd5o2eApmB4ikv2wbHFF2R1zwB+05rqomjjcEBnH2navvhlfSt3bG/BIUJEKTJtBn1RE7dhEFKKD+Vncfeiajw2XXfaG7uCYS59dxs7AiHsIpgKvju3nMsqCqe6aNoo9LddOyg919nHj7a3ELQU/aZF0FJ0REzCCvpMi5CleKmrn+/U7prqoh6QlFJc/M5WtviCBOLvsd+y+E7dLtb0+qa6eNoodFDQDkr31LcRsEafNj5oKVa2dhEd435aso2+II3BCOaw7UFL8ZvG9ikpkzY+OihoB6WOSHRc94sqRUjptvCJ6gpHsUnydgW0hiKTXh5t/HRQ0A5Kp+Vn45QUR61hqt0uMmy2SSjRB8vSbC+RFAt4uQ3h9MLsKSiRNl5pDQoiskNE3hORt0VkbXxbvog8KyK18cu8Qfe/SUTqRKRGRM5IZ9m0g9vVVcXkOWxJgWH3NRvgMYQ7FsyY9LJ9EGTbbVw/qxSPsef9dRlCidPB5eW6o3k6m4zsow8ppToGXb8ReF4pdbuI3Bi/foOILAIuAhYD5cBzIjJfKTW8WVLT9lmh086LKw7h1w3tvNjVR6nLyfnFubzWO8BbvX7mZ7i5pqqYhZmeqS7qAeuaqhIWZ3r5dWM7neEoZxbm8LkZhWTZ9ZnXdCbpXKNZRHYAywcHBRGpAU5RSjWLSBnwklJqgYjcBKCUui1+v38CtyilXh9p/8uXL1d6QjxN07SJEZF1SqnlqW5Ld5+CAv4lIutE5Kr4thKlVDNA/LI4vr0CaBj02Mb4tiFE5CoRWSsia9vbdRaDpmna/pTu5qPjlVJNIlIMPCsim0e5b6pev6TTGKXUvcC9EDtT2D/F1DRN0yDNZwpKqab4ZRvwF2AF0BpvNiJ+2Ra/eyNQOejhM4CmdJZP0zRNGyptQUFEMkQka/ffwEeA94GngCvid7sCeDL+91PARSLiEpFZwDxgdbrKp2mapiVLZ/NRCfAXiaX82YFHlVL/EJE1wEoRuRKoBy4EUEptEJGVwEYgClyrM480TdMmV9qCglJqG7A0xfZO4LQRHnMrcGu6yqRpmqaNTo9o1jRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMSdFDQNE3TEnRQ0DRN0xJ0UNA0TdMS0h4URMQmIm+JyF/j1/NF5FkRqY1f5g26700iUiciNSJyRrrLpmmapg01GWcK/wlsGnT9RuB5pdQ84Pn4dURkEXARsBg4E/iliNgmoXyapmlaXFqDgojMAD4G/GbQ5nOBh+J/PwScN2j7Y0qpkFJqO1AHrEhn+TRN07Sh0n2mcCdwPWAN2lailGoGiF8Wx7dXAA2D7tcY36ZpmqZNkrQFBRE5G2hTSq0b70NSbFMp9nuViKwVkbXt7e37VEZN0zRtqHSeKRwPnCMiO4DHgFNF5BGgVUTKAOKXbfH7NwKVgx4/A2gavlOl1L1KqeVKqeVFRUVpLL6madrBJ21BQSl1k1JqhlKqmlgH8gtKqUuBp4Ar4ne7Angy/vdTwEUi4hKRWcA8YHW6yqdpmqYls0/Bc94OrBSRK4F64EIApdQGEVkJbASiwLVKKXMKyqdpmnbQEqWSmu0PGMuXL1dr166d6mJomqYdUERknVJqearb9IhmTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtQQcFTdM0LUEHBU3TNC1BBwVN0zQtIW1BQUTcIrJaRN4RkQ0i8t349nwReVZEauOXeYMec5OI1IlIjYicka6yaZqmaaml80whBJyqlFoKHA6cKSLHADcCzyul5gHPx68jIouAi4DFwJnAL0XElsbyaZqmacOkLSiomIH4VUf8vwLOBR6Kb38IOC/+97nAY0qpkFJqO1AHrEhX+TRN07Rkae1TEBGbiLwNtAHPKqXeBEqUUs0A8cvi+N0rgIZBD2+Mbxu+z6tEZK2IrG1vb09n8TVN0w46aQ0KSilTKXU4MANYISJLRrm7pNpFin3eq5RarpRaXlRUtL+KqmmapjFJ2UdKqR7gJWJ9Ba0iUgYQv2yL360RqBz0sBlA02SUT9M0TYtJZ/ZRkYjkxv/2AB8GNgNPAVfE73YF8GT876eAi0TEJSKzgHnA6nSVT9M0TUtmT+O+y4CH4hlEBrBSKfVXEXkdWCkiVwL1wIUASqkNIrIS2AhEgWuVUmYay6dpmqYNI0olNdsfMJYvX67Wrl071cXQNE07oIjIOqXU8lS36RHNmqZpWoIOCpqmaVqCDgqapmlawriCgsRcKiLfiV+vEhE92ljTNO0DZrxnCr8EjgUujl/vB36RlhJpUyZiWgQje5fwpZTCZ5pY8cQFK359bxMZAqZF1DpwkyC08QuaFpG9/KxNSxEI6yTF/Wm8KalHK6WWichbAEqpbhFxprFc2jBRS/FwUwe/beokqhQXlORxVWUxXtvetQA+19nHz3e20hqKcEx2Bv3vd/LKuy2YlmJxeQ63nX8oSypyAOiJRPlFfRvPtPeSaTP4QmURF5bkIRIbhP67pk5u29ZMdzRKps3G0iwv63oHCCpFsdPBLXPKObckb7TiJKzuGeD/1TRQ6w/hEOGC0jz+Z96MvX6dE7HZF+An21t5p9/PXK+Lr1eXsjwnI+3Pu69aQhF+trOVF7r6KHLYuaaqmLOKcqe6WGOq9QX5+uZ63urzIwIner3MbArxRm0HeRlOrjpxNmcdWpbysRHT4va/b+bRN+sJRy0q8jx879zFnLKgOOX9tfEbV0qqiLwJHAesiQeHIuBfSqkj0l3A0RxMKalXvLuNV7r7CcRrVG5DmO9187cj52M3Us0QMrLfNLRx67bmxL5QCqIK16pWJGQBkOGy8cI3TiHT6+DUNTU0hyKE498VryFcWJrPDxdU8ueWLr5R07BnXyl4DOG+JbM4tSB71HJt9Qf58JotBCwrsc1lCCfkZvK7pXMm9Bon6t1+P+etryNoWex+do8h3Lu4mtMLc9L63PuiPRzhlNWb6Y2aROMfgccwuK66hK/OLJnawo2iOxLlmDc20Rc1Y3PZhE1cq9qQiJWY3MbjsHH1yXP4jw/PS3r89X98h6feaSIY2fNdcTsMHrvqWA6vnP4Bcartj5TUnwF/AYpF5FbgVeAH+6l82hje6fcPCQgAQUuxNRDin529E9pXwLS4bXvL0IO4CNiE6OysxKaIqXjkjZ38oaWLtvCegADgtxSPNXfRGAxzx46WUQMCQMBS/Gh7y5hlu6e+nfCggAAQshSregbYGQiN8xXune/WNeEfFBAgVu6ba3ftdRPYZLi7vp3+qJUICAABy+LHO1oYiE7fZpXHW7oIW1ZicjPbTh8MCggAgYjJL16qozcQGfLYHn+YJ94eGhAAQhGLu16oTXPJP/jGFRSUUr8DrgduA5qB85RSj6ezYNoea3t9WCm2+0yLN3oGUtwysm2BUMqZBzEEK9+VuBqOWtS09CcFo90chvBWn5/mYCTptlR2Bsc+qNf4g6Q6jDlF2BkIj+t59tZbff6U25tDYfxmqnd/enilu39IwN7NIcJmX3AKSjQ+Nb7gkO+VrTOIpIi9TrvBpua+IduaeoI4UzQnKqCufWK/By3ZmEFBRAwReV8ptVkp9Qul1F1KqU2TUTgtpsTpwCHJh3K3IZS7Jta1U+Swj9ypF9pzSHY7DJZV5VLpdqbseFJAqcvBbK8rxa3JFmV4xrzPsmwvjhQRK6QU8zPc43qevVXgTL2ek0ME9yT0Z+ytCrcj5faIUhQ70zmLzb45PMuL19jzvlpue/KUyMT6Dkqyh372VQVeIikCtSFwWIVuOtpXY37blVIW8I6IVE1CebQUTi/Mxm0YSTV8mwifLB1fB+5uxS4HJ+Rl4hweZEwL+7ZYLcsQ8DrtXLSiis9WFOIY1mdhEyh1Olie7eU7c8pxj9Gn4TGEG2en7jDcrT9qcml5QdLr9BjCecV5lLpSH/z2l69UleAZ9jo8hnB5eSG2FAF5urimsjip3A6BI7O9VHn2BOyopeiKRBPZYVPt/NI8cuy2RIXDrM6MffEGcdiExeU5zCoc2tmf6bLz+RNm4XEMDeQuh42vnjo3ncU+KIy3ClQGbBCR50Xkqd3/01kwbQ+XYfDEsrnM97pxG4LHECpcDv6wdA5FzokfLO9ZXM3J+Vm4RMiwGWTaDE5XTopDCq/TxplLSnnqK8eT63Uyx+vmN0tmUeiw47UZuAxhaZaXxw+fg4jwoYJsHjx0FksyPXgMYa7XxeERA8MfBdPC0Rfhak/2iFk8Nb4gZ66tYeGr73HK6s0ckuHh+NxMvIZBidPO12aW8JNDKlM+dn+6vLyAL1UW4TaETJuBS4RPlOTx7TnlaX/ufXF0biZ3zK8k224jI17u43KzuG/JLCCWGvyj7S0sePU9Dl+1gSWr3ue3uzqmuNSQYbPxj+XzObckl0ybQW6hh5NOqiTbbcfrtOG0GxxVnc9vLk/ZF8r1ZyzgxrMOoTzXjcdh45jZ+Tz+pWOZV5KV8v7a+I03++jkVNuVUi/v9xJNwMGUfbRbfSBERClme1yJlNC91R6O0BmJMtvjwmmMXj+wlKLOHyLTZlDuHrnJ6tZnNvLIGzsJDOoE9Dhs3PWZIzht4dBsmJ5IlKMHZ6AANqDC7eT1YxZOSQ3dZ5rUB8KUuxzkOKZv88twEUuxLRAiz26jeNBZ1U+2t3BXfSv+QU2GHkP4v0OqOG+cacKTKWJa7OjwkeNxUJyd3ibDg9lo2Ufj+tZP9cFf22Nwk8C+KnI6xn2mYYiM2a4fipo88kb9kIAAsSySO5+rTQoKf2rpHpKBAmACXZEoL3X1c9oYKazpkGGzsTBz7P6P6cZhCAuGfT6mUtzd0DYkIEAsq+p/d7RMy6DgsBm6tj/FxjvNxTEiskZEBkQkLCKmiPSN/UjtYNLrj4zYZr2rO5C0rS4QTJnZFFGK+mB6s40OBgHTGjLmY7Dm0PiyxrSDz3j7FO4iNsVFLeABvhDfpmkJ+RlOXPbUX6mF5cm1vyOyM4ZkoOxmQ1hyANbWp5sMm0H+CE1gC7y6aUZLbdy5dkqpOsCmlDKVUg8Ap6StVNoByW4z+H9nLEjKCnE7DK4/45Ck+59TlEuh0z4kDdUlwpIsD8uzveku7geeiPBfc8pTZlX919zp3YGuTZ3x9qT543MdvS0idxAbwDb9J4XRJt1lx1aTl+Hkp8/V0tIbZHFFNjeceQhLU0w94LYZ/P3I+dy+rYm/tvfiMIRPl+ZzXXXpPneiazEXluaTZbNxx/ZmGoNhDsn0cPPsMo7JzZzqomnT1Hizj2YCrYAT+DqQA/wyfvYwZQ7G7KP9xVSK13sGaA1FWJ6Twcz92IH9QWUqxavdA3RGoqzIyWDGKFlY6dblC7OqrgO3w8aJ8wpxO1IPvtO0VPY6+0hEqpRS9UqpnfFNQeC7+7uA2uTaGQhxwVt19MRTQaNKcWFJPj9aMEPX0Eew1R/kgrfqGIiPpI0oxeXlhXxvbvmkv2cPv76DW5/ZhN0mxP7BfZ89ihWz8ie1HNoH01h9Ck/s/kNE/pTmsmiT5PPvb6cpFGHAtPCZFiFL8efWbv7Y2j3VRUspbFls94fon6IJ3pRSXPbudlrDUQZMi4H4e/a7pk6eaZ/YhIT7alNzHz/42yZCUQtfyGQgFKU/FOXzD67Z67UwDiT+cJQdHb69eq1KKRq6/HQMpHdyxQPdWH0Kg6tAs9NZEG1y7AyE2OoPJU2w57cs7m/s4MLS6VXbvK+xndu2NWMpMFGcV5zHHQtm4BpjsN3+tNkXpCUUSZqbx29ZPLirg7OLJ2++ncfXNhCOpk4zfammjTOXjD6dyIHKtBT/88xGHn2zHpshKAVfPnk2/3HavHGdqa2q6+AbK9+hNxDGtODwqlzuuvgIPUAuhbF+WWqEv7UDlN+0Rhwp7DOnV03zmfYe/mdrMwOmhd+K1c6fbOvm5i2Nk1qOgGUNn5YnYWCS37OBUJRU8xkqpfB/gFcgu/O5LTy2up5Q1MIfNglETO55eRuPvFE/5mN3dvr4wkNraekLEohYhE2LdTu7+Myv35jW06JPlbGCwlIR6RORfuCw+N99ItKvB68dmOZnuHGnqGW7DOHcSazxjsdPd7QmDb4KWoo/tnZPagBbkunBGGGW2vOKJ3dU8FlLyvCmmNE1ailOmFc4qWWZLEop7l+1PeVI+btfGjvX5bdv7CQ6bFZV04Km3iDr63v2a1k/CEYNCkopm1IqWymVpZSyx//efX3y5yDQRmUpRXMoPGrbu02EuxZW4TEEe/w45zUMqtxOvlQ5NUsZKqXY2j5AQ9fQNQ2aw6lH3QrQO4425YYuP3VtA1ijLAIUtiw2DQRoH+G5AJyGwZ0LKnEbkmhv9RoGc7wuLq/Y+wNxyLLYFQwTGmHUcSonzy/i+DmFicBgSGwcyHUfmU9x1shNIfV9Qf62o4M2/4HXnh42rRHXYe70jT3yvaHLn3K6eEOgpXf6rjkxVQ6cGb+0Uf2ro5f/V9NAb9TEUrHptu88pIose3Kt8kMF2by44hB+u6uTxlCYU/KzOK84D88UrBuwdkcXX/n9W/T6IygUlXle7rnsSOYUZbI8O4N/dPQmtVt6DIOSUabS3tnp40u/XceOTh+GCFluO3d++giOnVMw5H6/a+rklrpdWMQysI7LzeRXi6vJTvGefbQ4l+cz3fy2qZPWUIRTC7I5pzh3r/o2lFL8745W7mlow1IKQ4SrK4v5RnXJmO3jhiH86rIjeWFzG8+814zXaeNTyytTjgMB8EdMTn/uPbY6FKIUqk44Wtn5y2mLMSaxX2ZfuOw2ZuR5qe9KXghpUdnYddNjZxfwypb2pDONiKk4bMb0XWp1qoxrnMJ0pccpxLzb7+fc9bVD5hFyinBMbgYrD5++88u394c4+UcvDmkLF4GCDCev3Xgav23p5Fu1u5Ied1xOBn9elrxuL0DUtDj+hy/Q3h8a0vbuddp4/hsnU5YTmz7j1e5+Lnt3W9J7dmxuJn84PL3rQd9T38YPt7cMaRrzGMJNs8u4aj+frX3kn+/wrs2EwQHftLjAlcEvTlywX58rnV7Y3Mo1v1ufWIJTAJfD4HdfOJojZ46eHDEQinLG/71MW3+IiBn7vD0OG2cfVsaPLlya7qJPS/tjjWZtGru7vo3QsNPjsFKs7vWlfW3jffHn9Y2Yw8qtVKyt+IXNbaxs6Ur5uHX9/hGXyPx3bQe+kJnUGRu1FCvXNCSu/6K+LWkyvrBSvNE7QFOaJ+O7q74tqa8kYCl+trNtvz5PMGryrs0aGhAAbAZPDhxYy1aeekgJD3/+aI6bU0BZjpsPHVLMH7983JgBAWKL8jz91RO5/NhqKnI9zC/J5NtnL+SHFxw2CSU/8Ojmow+A7YHkFFOILSXZFIpM29HKTb0BQinSK01T0d4fpMlM3c5vAN2RKF5b8ojitv4gZoo2+nDUomlQ+3HTCGtLO0Voj0RHXTNiX3VGohPavrd6wlFSL8gNUfuBN0hxxax8Hv3iMXv12PwMJ/919iL+6+xF+7lUHzz6TOED4NjczJRrG4eV4pA0r228L46eVZAykwaBZTPzOCLbm/KY5jQMSkZYB2JZVR6pWkS9ThvHDepTODEv9XtmKpiX5hlE542wrvX8ca53PV7Fbgf2cIrqglLkhQ/cZmMtvdIWFESkUkReFJFNIrJBRP4zvj1fRJ4Vkdr4Zd6gx9wkInUiUiMiZ6SrbB80X6osJsNmY/Dh1WsIV1YUkjeNVw87fVEJswozhky37XHYOHl+MYvLc7hxdhmeFGs2f3t2GfYRBg7MK8ni9MUlQ2ZqddkNKvO8nDVoYNdXZpaQZbcxuMIcW0u6FG+aO9y/O7ci5cyl351XsV+fxzAMrisriuVf7o6UlgJT8YNJWOJUOzClraNZRMqAMqXUehHJAtYB5wGfBbqUUreLyI1AnlLqBhFZBPweWAGUA88B85VSI+Ye6o7mPeoDIX64vYVXuvvJs9u4urKYi8ryp/1cRoGwyX2rtvHEW004bcJnjq7i4hUzscUPmhsHAty+rZn1fX4q3A6uqy7ljMLRM0ZMS7FybQOPvLGTYMTknKUVfOHEWWS4hgbI5lCYn+5s5eWuAUqcdq6tKub0Mfa9v7zRM8Dt25qp84eYl+Hihlnpm7n00S0t3FbbRI+hKFUGtx1axYcrC8Z+oPaBNVpH86RlH4nIk8QW5rkLOEUp1RwPHC8ppRaIyE0ASqnb4vf/J3CLUur1kfapg4KmadrETXn2kYhUA0cAbwIlSqlmgPjl7hy8CqBh0MMa49uG7+sqEVkrImvb29vTWWxN07SDTtqDgohkAn8CvqaUGm1qjFTtHEmnMUqpe5VSy5VSy4uKivZXMTVN0zTSHBRExEEsIPxOKfXn+ObWeLPR7n6H3cnZjcDg3q8ZQFM6y6dpmqYNlc7sIwHuAzYppX4y6KangCvif18BPDlo+0Ui4hKRWcA8YHW6yqdpmqYlS2e+4vHAZcB7IvJ2fNvNwO3AShG5EqgHLgRQSm0QkZXARiAKXDta5pGmaZq2/6UtKCilXmXE8ZScNsJjbgVuTVeZNE3TtNHpEc2apmlagg4KmqZpWoIOCpqmaVqCDgraAacnEmXDQCCxwlx7OMLGgQDBEabT1jRt/KbvbGmaNkzUUtxU28jK5i4chhCxLEpcTlpDERyGoICbZpXyhSlaVlTTPgj0mYJ2wPjRjhb+2NJFSCkGTIuQgvpgOHHdZ1rcuq2FZzt6p7qomnbA0kFBOyAopbivsT1ptbThApbFXfX7dwUzTTuY6KCgHRAswDfOPoOWUOpV1TRNG9tB2aeglMJvWnhsBkZ8vQF/OIrTZmBP8wIrB6uoaRExFZ5UK62Ng02E+V4XNf7R15y2AyfkpWddghc2t3LvK9vo6A9xyoJivnTyHIqyYqulBU2LB3Z18HhLF3YRLikv4JKyghEXAzpY/K29h181tNMViXJGYQ5XVxZT4DwoDzsHjElbTyEd9mY9hcdbuvj+1ia6IlG8hsHHbW7Wv95Efacfh1248MhKvn32Qlz2vTt4aUMFIybffXoDf16/i6ipmFWUwQ8+cSgrZo294Ppwr3b1c/E7W4koBSKxVcQGHXTtQIbdxvNHLWDGfl5j+VevbOXOZ2sJRGIZTw6bkONx8I+vnURehpNz19fy/kCAYLx5y2MIJ+dl8eBhs/drOQ4kP9rewt31bfjja2Y7RShw2nnxqAXkTuMVAQ8GU76ewnTx9/Yerq9poC0cJaqgvzvEn56pY3uHD1MpghGLx9c28I2V70x1UT8wvvLoev68fhehqIWpFHVtA1xx/2rq2vonvK+6TR24V3dgtAURXwSjNYB3Uy8LbA7meFxcXFbAC2kICAOhKP/37JZEQACImIq+QJT7X93O8519bPIFEwEBIGApXu7u560+/34ty4EgGDGp6Rzgrp0tiYAAsTXDuyJRHtzVMYWl08ZyUIXrH25vGdJRadvej7LUkAmaglGLZze20tYfpDhr+i56fyBo7Pbz79oOQtGhfQFh0+LeV7ZxxyeXTmh/P3+hjogvjLN7TxOSBZj9JqtuOHV/FDmlmpZ+HIZBkOTX8fKWdoJzs1L2d5gK1vQOcES2N21lm04ipsX3nt7I42sbsIidzNnmZ2POyEjcJ2QpXuzq52vVpVNXUG1UB9WZQmMwPOS64YuknLHPaTNo7A5MTqE+wBq6AjjtyV8x01JsaR2Y0L5MS9HpC6e8raU3uFflG6+iTBfhETq5y3LclLocuFP0HTgNodjpSGvZppPvPrWBx9c1EIxahKMWRCzsm3ox2ob+lrJ0v920dlB9OvO9Q2v+Vo4zeWk3YjXA2YUZKW7RJmJOcUbSWQKA3RAOr8yd0L5shlCem/rMrTrNn1VVgZfDZuTgsA098HscNr544mzOL8nHJslBwS7CGYU5aS3bdBEImzy+rpFgZOjnLZbCvnVoU6GR4r3Spo+DKih8a07ZkBqdOSsLSfFDv3hFFbne/dsufTAqznJz/hEVeBx7vmYCuFw2Fiwt5um2HnojUXoDEf7+XjPPbWwlGBl5CY2bzlqI2zH0K+t2GHzrowvT9RIS7r1sOUfOzMNlN8h02cl02bnlnMUcPbuAQqedx5bOoczpwGsYeAxhlsfJX46Yi+cgqRV3+cMjHuwlOPQz7YnqZVKms4Mu+2hVdz/f39pEjS9IucvJJVlZvP7GLtbu6CbX6wsN6yUAACAASURBVODKE2bx+eNnYYwzlbA9HOGv7b0ETIvTCrJZkKH7IQYzLcWv/72NB1Ztpz8YZe7CAjaUOzEkNi1FyLSwb+whoy3WT6BQ3HvZco6fW5hyf//a0ML//quGhq4Aswoz+M+PzKMvz0lLKMLynAyOyclAxlkT3ewL8P26Jlb3+sh32DmrMIc1fT5qfEEq3U5umFXGmUVDa/rNvQG6fRHmFGckZaht9wd5pLkLh8Dl5YV0RqK83NVPrsPO2UU5E8q46YlE+Wt7Lz2RKKfkZ7Eka3r0S7zf7+f7W5tZ3+ej0GnnP6tK+HRZPqalWPb9Z+kLRofcXwFWkYvIstjn6TKEL88o4qY55VNQem230bKPDrqgsD/9o72HL2/ciQBRpbCJ8NmKQm6ZWzFlZZrOfFGTw17bkNwpa1o4X2/H8MUOKF6njTdvPo0s9+jt8ZsGAnzirToiliJkWTgNgyNzvPzusNk4jdFr6Nv9IU5fW4PPtFI2IUIsrfSOBZVcWDp2+uzPd7by4x0tsSxZYpk2NkAJOMRAgIcPm8UJeVlj7uvV7n4uf3c7CogoC4cI5xTncechleMOeOmw2Rfgo2trh2QUeQ3hKzNLuK66lEfe2Mmtz2wakqWFTQgdXYTKcmADchw2Xl5xCEUHUV/LdKRTUtNgIGpy9cadBC1FwFJEFAQtxUO7Oni9Z2KdqAeLZzv7Ut8gglnm2XMVeG5T66j7Ukrxxfd30BM18VkWUcBvWazt9XFf49gpjz+rbyUwSkCAWFrp97c2MVbFabMvwI93tBC0FGGlCCqFBUSAqIpNveG3LK58fwdha/RR2WHL4vPv78BvWQQsK/54xdNtPfxjiud0+vH2VoLDyu+3FD/f2YrftLj0mJncedHhLC7PpiDDyYcWFHHNp5YwuziTIoed80vy+NfyBTogTHMHVUrq/vRiV3+8c3HoASNoKR5v6eLY3PSMqj2Q+U0LK9UBVoBBWUqmUvjDo7c71wfDNIaSs5ECluL3zZ1cXTX6TKnre/2Mp2W7KxLFb1pkjDKY8em2HiJjzMkEsde1utc36tnC6l5fyiDktywea+7irKKJddDvT+/0+0kV0gwRdgXDzMtwc8biUs5YPDTd9PrJKZ62n+gzhb000iFAjXLbwe6k/KyUBxVMhdG+J61UKThpXtFeP8943v/ZXteIC4gP5jGMMTuLzXF+4ON5vtFOSqZ6tYhqT+rki6ilKHHp2v8HhQ4Ke+mU/CyiKX7BXsPggpK8KSjR9DfD7eSrVSV4DEkcIG2WwtEVxugMIcSyv646aTaV+aN3rFa5nZSmaIZwG8KnxtEH8B8zS1KOLRjMYwjXVBWPmUL58eJcHONITFDAUTmjp8+uyM1IGdS8hjGu15VOX68uxTPsdboN4YLSPLL1tDAfGDoo7KVsu407D6nCbQhOEQxiB5FPluZx/F42HT3T3sNpa2pY9Op7XPLOVjYMjDyArisS5eYtjRy26n2Wv7aB/9vRMmZ79XTwzVmlrDx8LheX5XN+cS73HTqLBw6r5rzDy7lw+QwevnIF3/jIgjH3IyLcu6SaLJuBJ96pnGEzWJLp4Yszxj7LOCLby6+XzGKGy4FDBJchzHI5htTmj8zO4D9nloy5r8WZHq6uLMZtCHbAIbEfloN4Cq4heAzh3sXVuMboAHcZBvcursZjCC6JBU+vYfDhgmw+VjS1Yx6Ozc3kFwtnUhZ/zzyGcGl5AbfPnzGl5dL2L519tI+agmGebOvBb5p8uDCHpXuZOvhAYwff27orMQ2HEGu6+OuR81iU6Rly34BpcfLqzTSHwkTiH5/bEI7LzeTRpXP25eUccPqiJk+2ddMcjHBUTgYn52dNaHCUUoreqMmfWrr4Vl1T0u1XVhRw6/zKce1rsy/AP9p7sYlwdlEOnRGTFzv7yHXYOa8kd0IdrO3hCE+09tAbjXJKfjZHZnunNPNosN3vmddmjJnlpU1POiV1motYikWvvkf/sFRNAT5SkM1Dw2ba/H1zJ9/asmtIaiDEzlSeXDaPw6Ygp70xGKbWF2SW10W1xzWpz71pIEBrOMKSTC+Fezkt85xX3k05f5EBNJ58GIY++O0VpRTv7eqlNxBhaWUu2WOkGWuTY7SgoLOPpoGWcCRl/4QC3upPnmVzTa8vKSDs9m5/IGVQUErxVp+f7YEQCzM9SWcfeytiKb66aSd/7+jFKUJYKY7PzeQ3S2bhTfNo3vZwhEvf3cYWXwi7xMYGfLGiiG/NKZtwrXqkBXwsoC0cpTTFzKtB0+Ll7n4CpsVJ+VnkT6PpoLe09rOxqY/KfC/LqnKn5CyjvtPP5fe/SVt/CJsIYdPi+jMP4coTZk16WbTxmz7f4oNYvsM2YmbJDFfywWi2x4XbkCFTNUNsIZoZKWpivZEo579dxxZfCIVCEA7P8HBit0Vbb4gT5hZy1qGle7WGxJ07WvhnRy8hSxGKd5Gu6hnglrpd3LFgfM0ue+tLG3awYSBAdNDbcP+udpZkeThvgp39dmHIfgbLT3H28XrPAJe8s42IUon39Ltzyvl85d5nTe0P4ajF1b9bx6q6DmzxUeNV+V4e/eIx5GdM3tQtSikuv/9N6rv8DP6a/u8/a1hSns3RswsmrSzaxOhz4mkgw2bj06X5SZkdHkO4blbyFMOfLsvHPqzmZwMKHHZOTJEDf83GnWwYCBJRiqiCiFKs6ffx85YO/riukZv/8h7n3LUKXyia9NixPNjUkbRucshS/KGlK/WYhP2kNRRhXa8/6UDutxT3NLRPeH8Xl6TO7DkmOyOp3dxvWlz09lb8ljXkPf123S42pDizS7eAafFoUyeff287F/xpPf+u7SAYsfCFTfxhk7q2Ac7/5Squengt97xUR48/9Wyz+9OGpj7a+kMMH74RiJg8+NqOtD+/tvd0UJgmbp03g4vK8nEbgtsQ8h02bps/gw8XZCfdt8jp4M9HzGVBhhunCA4RjsnN4Illc5Nm64xaihe6UixoI0KkPJYe6Q+b7Ojw8cCq7RMu90jNLhFLpWwS21/6ouaIS132RCYe3H60sIqzCoe+18uyPPzxiOSO+ydauwmleG0W8OMdLRN+7n3hM03OWreFb9c28reOXt7d2B6btnqQqKXY0ennXxtbufP5Wk798cvs6knv1PC9gUjKmWOBEadA16YH3Xw0TTgM4bb5lXxnTgV9UZNCp33EHxXAYVleXl5xCB3hKA6BnBHaswOWOfJgrkFVglDU4ql3mvjKqfMmVO5jcjN5uas/6TkWZ3rSmpky2+vCZQi+YcOSHQIfKUwOpOPxwKGzCZoWW/xBqj1Osu2p39O3RzkbqPGld22H4R5s7GBHILSnKXGMkXTBiEU4Gua2v23irs8sS1u5llbmEknR7+V2GJy5WC+wM52l7VcrIveLSJuIvD9oW76IPCsitfHLvEG33SQidSJSIyJnpKtc053HZlDicowaEAYrdNpHDAgAHsM28kjaYef2bsfE+xS+P7eCTJuBM/4kdonl1f9wQXpz120i/Gh+JR5DEl9ilyEUOOx8dRxjC0bithkcluUdMSAAHDpKJ/1c7+TOkvtke8+QviWz2D3miG5LwUs1E29im4hMl52bzlqIx7Hn++d2GMzI83LRivT2NWn7Jp1nCg8CdwEPD9p2I/C8Uup2Ebkxfv0GEVkEXAQsBsqB50RkvlJKT7y+j+yGcFJeFi93D2tCUgpj154ar8dh47JjZk54//My3Ly84hB+3djO231+FmV6uKqyiJmTkJb6seJcZnqc/Lqxg4ZgmJPyMrmiopC8NGcBnV+ax821jYkxIrsZwDeq9z4g7Y1s29BAHp2fg60zFOs1H+WsYfi6FOlwxXHVLC7P5sHXdtA5EOaMxSV86qhKvHuZNqxNjrR9OkqpV0Sketjmc4FT4n8/BLwE3BDf/phSKgRsF5E6YAXwerrKdzC5e/FMzltfy/bAno4/W1+EzB0D4LRhWoqPHlrKBcv2rnbviipyd/jJa+whp9TEVVII+yfjNUlLKMIDje1s9AU5PMvD5RWF/HRhVXqebAQZNhu/XzqHS9/dRnT3GyrwrdllHJY9uSv2fX5GIev7/HtSlF02IieUUNwW4gRc1LT2s71jgMHdDG67wWdW7HnPVvcM8EhTJwOmxTnFuZxdlDtif81AKMrjaxpYtbWDGXleLjt2JnOKRh7Bv7w6n+XVUzs9hzYxaR28Fg8Kf1VKLYlf71FK5Q66vVsplScidwFvKKUeiW+/D/i7UuqPKfZ5FXAVQFVV1ZE7d+5MW/k/SJRSvNnrY1sgxMIMD4dmuPl3XQft/SGOnJnHDsPigV0d9EdNzinO5TNlBeNaNWxnp49z7lpFMGISilo4bQYOu7DyS8eyuDw2LcPrPQP8pqGd9kiU0wuy+WxFIVl7kf66aSDAOetrCcWnqHaJ4LYZ/P3I+cz2pj4zCVsWb/b4sICjczJwD3tN7eEIb/X5KXY6WJrlScrn3+wLUB8IsyjTQ4XLwVv9fjrDUZZlZ+C2CS909hO0LE7Oy6J4HyaFU0qxsbmPlt4gSypyKMkeXzOUUorvbW3i/l0dOOIpqLl2G386Yi7VHhe9gQiX3/cmW1oHsBkQNRUnzCvkl5ccidNu8POdrfwkPu23Itb0d2SOl98fNicpMHT7wpz981fp8oUIRCzshuCwGdx96TJOWTD6rLTa9DJlI5onEBR+Abw+LCj8TSn1p9H2/0EZ0TzVbt/WxL0NHYnapscQ5nndPH3kvDHn6rnywTW8WNOWlHp4eGUuT1x7PPc3tvP9rU2JtFW3IZQ4HTx31IIJB4aPr9vCmr6hnbwCfCg/K+X0Hv/u6ufK97cPGQPyq8XVnFaQjVKK27c1c09jO04RTKDC5eAPS+dQ7nbSFzW59N1tvNfvxy5CyFI4DcGKL6YUVoqvVpXwzRQpwxPVORDi8vtXs63dh92IDfL69PJKvnvu4nEPOmsOhVnT66fQYSdkWXx/axO1/hAlLjvfrC5lsWlnZ5ePQ0qzmVscq9m3hyMsf30joWEfntcw+PmiKj42bJruHzyziQde205kWLNUUaaLN28+bdyrFWpTbzotstMqImUA8cu2+PZGYHDv0wwgeSIabdxe7e7n9DU1VL30Dke9vpFHmzpTztPfFopwd337kBHSAUtR5w/xZFvPmM+zamtHUkAAeLexh55QZEhAgNh6E63hCA/uGnshnMFMpVjbl5z1o4BXu5MXNeqORLn83W30mRYDg/5f+d422kIR/tbRy68bOwhZin7Twm9abAuE+Ox7sbTcb2xu4O0+P4H47WGlGDAt/PHrIUvxy/o2nt0PC9/8x2NvUdPSTyBi0h+KEopaPL6ukcfXNox7H2UuJ+cU52Kh+Nz729noi41LaQxGuGlLI6sJc/Zh5YmAALCqeyBpvAvE1m54JsVn/8+NLUkBAcAXjrKj0zfusmrT22QHhaeAK+J/XwE8OWj7RSLiEpFZwDxg9SSXbUR9UZNaXxD/CDn5080bPQNc9u423hsIEFaKhmCYb9Xu4leNyRknb/T6Uk777Lcs/jmOA97ujCXLa8MsdmNlxLqprGwHZ62v3dPmPkjQUuPa92AGYBuhIprqwPZUWzfBFEEwqOBPrV38uqE9aaoQU8EWf5AaX4B/dPQSHuMs2m9ZfGNzA599bxt/ae1O+VrH0jkQYs325McGIib//dQGTv/Jy9zxj83jHnD2g63NSSPdA5biR9tbMIe9ngybkTIzLfZeCw3B2HNaSrHNH8KVIjtNOQ18MzP4f/XN3Lq1ieYUCx+ly2ZfgBtrGrjkna3c29DGQFTnpewPaetoFpHfE+tULhSRRuC/gduBlSJyJVAPXAiglNogIiuBjUAUuHY6ZB5FLMVNWxp5vLULu8SaDr5SVcJ11SXTZsbKVG7b1pw0yjhgWfxkRwtfqCjCbghKKd7uD7DNH0w58tgGFI8jS+QjR5TxiH8Aq8AVG71lEKu+i7A9OPIBYqJLMorEpihPNSDOmaJq81ZfYMTUzPV9fjpHGOCmFHSEIuMejd0WifKPjj5e7uznseZOHl06Z9zpxBAbOGgzhFTLwAUiFrVtA+zs9PHUO008fOUKvA47pTnJ/Q2mUjQGw2zxpx4n4TcteqPmkPmZTs7PigVUS2H0hMFUWHlOlN3gybZunm7vocBhw28qQpbCLLRjaxes+NmC5bUTPqYIsQmr+nys6ffzwK4OnlqWPLPvSJRSNIUiOA2Z0Hfinx29fHnDDsKWwgRe6xngN40d/Gv5fHKn0RxUo1FKTcvjSDqzjy4e4abTRrj/rcCt6SrP3vifrU38qbVryLw+v6hvo9Rl55Lywiku3chGGkAVshTd0ShRpfjU21tpCkUwiE0NMZzTEC6Pv8aIpXhoawuPb2gmy+Xg60fN5Pj4ALGX8wXL445V43dXJJWCwV/2Ydc9hvCFGYWDbo41VzkNGTGV1VQqZTkB+oeN4FVKjToZn9dmkDXC7SHL4qIf/xvr2GLIGP9BKqAUr3UP8FxnH2cUjn/dg4pcD1lu+9DF7ocJm4pdPQE+/OOXcdgMZuR5+NnFRyQ68p9u6+aGmgZ8pkVohFjmMiSRvrrZF+DBxg52hSJ8xO7iqWcbUbubhZQiujCX8IwMUIpdoSgEotg6QyibYJV6sDUHyHTY6FmcC3ZBxT/bsFKETcUNNQ08feT8MV/7+l4f127aSVMoglKwJMvDrxZXU5li8kGITVP/wK4ONgz4ea3HN+SMKGApWkIRflnfxs1zysd87qn0++ZO7tjeQnMoQoXLwc2zy7hgihdQGuzACKlTIGopHk4xr4/fsvjZzrZpHRSqPa6Uo27tIuTa7Xx8fS3bAqEhaewCOEVinanAD+fPYGGmh4ilOOGRN2jd3JX48V+yqoFLPr6AW4+ew85wNLldZ3jtRwSUIstuI6IUN88u4/j4HE1v9gzw5Y076Y2YKBQz3E7uXzKLeRlDa8M2EYocdtpT1PBnxA8iPtPkltomVsYDeSo24MS8LNb1jjAq2VRIhgPH+z2EjywAQ2L/LRV7kxSx6ylEgD80d00oKBiGcMcnD+PqR9YTjpojDi1QKvbUoajF1nYfn/7V66y68TS2hsNcs2EnkVGewwZ8uTJ2hvhMWw9f2bQzVsO2FK6XWpCINaQZyb6pFyvHicpyYNvSi33nwJ7PVCB6WC7Xzq7gVl93yudb2+fHUmrUdS3awxEueKuOwKAzsvV9fs5ZX8vaYxclnW293+/nvLfqCMczzwDEH8XW6IOgiSpwES718reO3mkdFH7f3MnNWxoTx5VdoQjfrGnALsK502TFRj330QgC8cnOUunYi7l1JtMNs5KXTfQYwpcri2kJR9jsCyQdfBQwx+vioUNn8/7xS/hkvOby07fqad3cDRaIqRBTQVTxyNM1tAYm1n784KGzeP/4JXyxMpa+2BaKcPG722gORfBbVqKD+xNv1aVcRe4bKZaD9BjCDfEMoM++u33UgGAQGwF+dlEuFSPN6y+ChEyMnjDO19qw1fuQjiC2rX041nSQ0RmiYpRmtV2jNJmN5JQFxTz91eO5aEUVh1eOPEZgsEDY5Mm3Gvne1qZRAwLEjudt4SgRS3FdTQOBeJOL0RlKGtUOgKWwNfowOkPYd/qQQZ+9RBW2DT1kl3nx2lMfPpyDllsdyf0N7UMCwm7NoQgvdvYlbf9mTQMD8Q5/AKMjiHNVG7YdA9ibA9g39eJ8vY3Mab48zA9TNu0qbtvWPEUlSqaDwggybQYlI7RxHjEFi9hMxIcKsrlr4UxmuB0YQI7dxterS/lmdQkDUXPENu+IUhyXlzlkfMIf1zagUhw4RMFD7+2ieoRT/SGUwt4f5fi8LDIHpaGubOnCHLZvBQQti+dSHBiuqCjgO3MqKHDYMIj1edw2fwbnl+az2RdgTZ8vKSBI/L+NWBv6M0fOx20zuDa+VvQQlgKlCJ1USvCkEqw8F46aXlzrOrHv8EFlBsEiNy3hKCN1WFSM5/1IYW5xFrd+4lD+cs1xzCrMGLFTfTdTwbr6Ht4fZcnW3aIK/tDSxXv9/qGdzdHUiRMCELEwGn0jBA3Y2tTPJWUFSetcu+JrZI/VVv7MKIkG/2gfelvYsni3f9DrVArHe92IpZDdYwdNhRGIMrNl3zu6lVI88sZOjv7Bc8y5+W+ccecr/Lt236cFsZSKfXdSaJjEDvqx6OajEYgIt86r4OqNOxOR3QDchsF35k7f09PdPlacy8eKcwlbFg6RxI90nteNI8UP1inCR1M0e9jirSap7PKHuGVxOV/YsGPPFNbWoAfEm41QcHxv6lphqtlGI5aiddCPp70/xOaWPspzPXxuRiGfrSggotSQCfe2+UM4RAiSHGROzcvk4WGDsU7Kz+KWuRV8b2sTAgxEzFi5d9d+PXaiC3PAgNz2ED2LcrAK3XvGPKR6U6IWZ+YmT10+ESLCI184mi/9di2bmvsxLTViVlM4auEy7AyMIyXDVLFWr8Ed9Va+K/b5DKNsglXswdbkH/GzL7XbuXxWGbX+EK929+OIJwEclZPBLeP4ffSNkinUGhl67mMTwR4fGwIgvmjqKTws2Lo1dZPWRPzqlW389LnaRD9PTUs/X3x4LQ99bsU+rQNhiFDmctAcSj63q9rLykQ66DOFUZxZlMvvl87hpLxMKt1OPlqUwzNHTs1yl3vLaRhDam12Q/jxgthEcrtro25DKHE5uLoqeVTqJcsqU+aCKqV4xgxy9cadzPe4+UxpPksy3dgVsSykRBt0LDCY85JnLj02N5OMFB2+hsBR2V6UUtzy1AZO+OELXPPIej72s39z4T2v0ReMJs3AOj/DnbK5z2UIh+dkpGySuaKikA3HL+GJI+Zi+KPJfSF2g+i8bK4/bzFGiRdr+D6U2nNQjVrYeyO01nUlPc9ElWS7eeLaE3juupP58smzR+rCYGFpFh8fNsBsJEVOO0uzvMzxuvb86F02orOzUDZJhFJlE1S2g4qqbPJnxm4bToDPLC7DbTN45LDZPH/UAn62sIp/Ll/AysPnkmEbe1Di3FHmxhq+zrlNhPNK8nDu/nxskjKYAXhd+1bPjZgWd71Ql9TxH4xY/O+/avZp3wA3zypL2QR68+yyfd73/qLPFMZwTG4mKw+fO9XF2K8+VpzLbK+L+xrb2RWK8KH8LD5TVjCkaWe3Ly2v4i/rG6lt6E3UzpQBkUW5hAzAUmz2B6kNhGIH5VTtHjaDN4LJGVFnFuYwx+Niiz+YyCTxGMKpBdksyfLy6Js7+cOaBkJRi1C8qePthh6++fg7/PryoYMx53rdnJCXxavd/Yl9CeAyDD5XMXJSgNtmsCTLi5HhSLn6nTgMqmfm4Hq/m/Dw2qkIhGP9D7aWAEZLgB1H7PtEgH7T4r9rd7GytYsw0VgTzbDndtkNlh5SxIlZTp5s76EnMnSK9N194hB7T2+bPwMR4cFDZ/Opt+toC0cxgNCcbNyFHkI7+yGqcJZn8LNTF3BWSR6mpfh4x2ts3P3ZC4gh/Nc5i8kc1Cczx+tmzgRnh715TjkfXV+btN0AvjwjefW6H8yroD4Q4p1+P/ZMJ5EMB/QPrXG7HQazCjP4xYt1nDy/iCUV4+/w363bHyYywnik2rbkQZITdWFZPiJw+/ZmmoIRqtxOvjW7jI8XT49OZtBB4aDli+et90ZMeqLmiAO1bIbwz6uO4++bW3js7SbeDgToKHahMvccFCwYktcvfRFsO/oxfFGsPCfR6ixMd3LAsRvCE8vm8ZuGdv7Y2oXTMLisvIBLy2On6Pe/uj2pxhYxFS/VtNEfjJA1rLP4viXV3L6tmUebuwiYFsflZfI/8yrGlf8+J8NFjT+UtD3bbmdxpif1+2MpbM0BHJtjbeBep41lVfv+4/78+9t5vWcg1j/itBFamo/j7S5k0OR71qIcPre1AQtFpcvJ6QXZrO31U+y084mSXFb3+lnf52e2x8nXqks5Kic2UV+l28lrRy9kbZ+f9nCEI7MzKHE52OYP4TdNDsnwJM6qbIbw16uO4/maNv707i7yvU6+cEw1s0eZAG+8luVkcPPsUm7f1pIIxnaBB5bMIjPFOINMu40nls1j00CAbYEQOXMquf7h9fQGI6AgbFqEoxZ/f6+Zv77TxF0v1HLeERX84BOHTmgsQJ7Xid0Qkr8JMLtw/0x2+MnS/EQix3SU1rmP0k3PfTSyV7v7+V5dEzW+ICUuB1+eUUhUKWr9YaJK8Ze2bkLxSdCcIuQ5bDx31IIxD6CLX32PzlFy6o32II63u8BSsdqqADah+EMVrDlt6YRew1G3Pkd7f4qfpyFwcilVuR6ury5lezBMYzDMsbmZfLQoZ9yL++wIhLh9WzOv9QzgMoSWUGTIdNgeQ7hxdhlfqizmv+t28fCuQSnKKjY1tXN1B0QsHGGL4iwXz113MhkTbMJQSvHgrg7uqm+jPRyNr/s8TNjEXtOLrT1I6Nhi8Ox5DgModTlYE0/lDFkWz7T38nafn9leF+eX5GEzFW39Icpy3Hu1bka6dEWivNzVj8sQTsnPHnV8yXCmpXh9ayeN3X5ueXoDwcjQGr7XaePuS4/k5PkTWzf7Z8/VcvfLW4dUSNwOg/uuOIrj507fVPSJmLIJ8dJNB4XU3uwZ4KJ3tialvtmJDRdPxSHw2fJCbphZSuYoB7VF/36PrpE6CZXC9UorEhx6uwLMUg/Rpflk2Qx+fEgl5ww7XfaZJgYyJPPpm4+/w1/WNyanz7oMQieXJvoAdr+uDJtBldvJX5fNI2NQU9ju6UkGH3AagmFOW72ZAdNK1FSdElsKtc+0KHTYua66hMvLCvCFTbJcNh5u6uSehna6oyaHZbqp6fLThgUKMhDuXjSTj5SP70zhqdZufrCtmcZQmEybDX/UZKz8E+kMYnSHMWdlJTXTZdoMfr24msOzvZy1dgvtkSg+08KNYNvcg22XP3EGcO2HFfN6DwAAIABJREFU5nLNKXPGVYOu8wf51pZdvNYzgMdmcElZPjfOLhtzosTJ9NzGVr72h7cZSLHG+LmHl/PTi46Y0P6UUvzm39v55Ut1dPsjzCzw8l8fW8SHF03uWhnpNFpQ0M1H/7+9845vszz3/vd+Hm1Z3jPDcUISx9khAZIQQlgtUMoqLaQtLz0ddNBCd0s5b09ZpeP0PfR0QGkLlB5KDy07ZYU9ApkkZMdZHnG8LQ/NR89zv388smxZkuNMC/J8Px9/bMmWdEmW7uu+r/G7PoT8NE0tNGR2CACahD/tOsgjD77P5NIcfnHVbGaPS01i5tnUzE4hakA09XcCUDsixIBe3eD6rXUU220sLvCxoy/E57fsY1+852GOz81fZk2izGnn2xdM5eXtLQSiujl3WIAUAm1GQVJSOGZIMCSBuEbPPQ2tfHdiBY3hKDdtr2d1txkLnp/r5dc1lVS5nfymroXAIIcAZkeuIqF2yUy8qso3V2zhjjVrMXSJ3aHytQum8O6S6ehScsa72+hQJP1lSAHgK7UNvF3kpcLpQDckL29v4eUdrRR6HCyYWcrD/m7W9wRwCkFzNJYISflHotmjS5TuKNKtggJKPIeBCrFxXqKFLu7Y3YSGKXfR/7+O7fQjGwLohkw4nd++spviHAdXn5Z+DsXBSJQX23vo03X+a38LfXGnqsV0/tzYTm0wwv/MnnRom9PQHo3xfHs3mpRcUJSbaDzMJoQQfGnpJL60dBKGIU869VfLKXwIOeI5wbpZ/rijuZfl973Ly99ZlqKzU+SwZdY0UkXG+n1pT/5g3VzbyFNzJ3P+up0D5azAxt4QZ63ezvazZjEm383Kb5/Ng2/v5929Hbwbi6BPyEH64iEuQ5ohlcYgSIl0qmg1eTzm7OLGCWVcsr6WtqiWkBVa2x3gkvW1rFk0ndc6e9PJDRGTkr3hKL99aRcr1zYl6vS1iM6vn92Jx2Vj2qRC/JqecntdSh5u6uCmyjKuu38NGxv8BKM6is/Of9mCCJtyyFGZ6V88CQqoTUGzy/hgCMUfRegSQxWIiT6iusHWYDhZUkRK1IbAQC4iTkjT+d2re9I6hQca2/nJngMokOh6Hlz+FJWSl9u6mf3LVxhjt3HDOZP5+JyRlWg/3dLFjTvqURAYSH6y+wA/mFjO1yqPbgd+5uTitFpVHofKlUc4OKqfk80hgFWS+qGk6khGYUqZ1Kik6ZK/vrs/5c9a09RY92OzK9jLPWYeYfBdKwK9Kjk52RCK8ot9LUkOoZ8e3eAfzWZpZ3GOk+9+tJr//fJCYjMLBhwCYNvmR20MJJqYlLCOfVMX/qY+no/vdAcv3AYQ0g2eafUTzlBhEpMgdYOV65pSG7cMyd0v1XIwEk3b0xWRkvpwlKc3NvFevekQAMKTckARR+YQwFzkDdBL3SjNYZSuiNlZDujjvfHTw6AS4H50mb75DGjvS83V7A9FuHXPASKGNLuew7G0kh5Sl3Sp5ubh+/98n/ve2HPIp9ARjXHjjnrChiRoGIQNU2TvF/ua2T6CBrzhcDtUfrN8Hi67gsumoCrgtitcNncMS6d8OHIAJxLLKXwISSdzcUiEgEFze6O6we40JXixYZa2tQtryJ9XglHoRCogbQKpgD7Ogz4uuXJjjNPOu92ZS/xe60yeKa0qCtWDp6tpBurBIGLo2m5Iotu6qAtF0i78AcOgLhTBlSEmrgJNoWjaLm6AUF+UeblejDSvg0dRWJyfw9ObmpKSlEa+I6Ne0ohRBe4KL3a7kvScjXI3ZErOqgKc6X83K0255jOt/qSOZ9EVTd8kpsQbyDBPHXe/VEt4mOIDgBc7utNqIWmG5MmWo284O6+mjDe/fy43X1zDty+o5h9fWcxdV87OShXSbMdyCh9CzinK5Tc1lYxzmjIXPlWh0KbiUQSuTJ8RQyL8A2Ehl11JW14pM/S4qsC+cJRWQ0dbUEz0zDK0eUVEzi4nVpOf0hh259TxVLozx5MnpTnt/GPuZPLjCWQR0VObzTAj/EpYZ0aOG2eaxdKrKsz0uTmzMCftM7EB09xORAadCWeek2qviwuK8pIcr0MIyp12ListwD2kukeEDp0zsAlwigFZjqGowJXVZcycVpTsjjJIVSAlNiFQpxckJaWFALdd5UcX16TcRDNkUk+Y0hVJbtAD0A1EVxQlMJChEkBjVwaBwf6bSdIOeTLgkHMrRkqJz8l1i6u44ZzJR9SjYGFy0uUUDGkOeHmm1Y9XVVk+ppBThxm23hLReKipnV2BMPNzvSyvKCTvBOm1b+8L8T9NHbRrMT5anMfHS/LTDsRJx0yfh6WFPtb4A0zyOPl6ZSkRQ7I3FGFtd4B/tfmTyysNiW2vuXNXBHgdNq5JE3PO1KZvU0wV00RnrMeG9KS+Tm5FcOeUcZxd6KPUYeOF9p6UPbcCfHV8ahlhqdPO1iUzWdnezYauAH9c1Zr23FJTkcuyQh9VLge1wUhi0bHHZQY+UpRHjdfN061+AoNOE86mICIY46zm91GqclDqA4jooEVXEXz5PLOR8Z7pE/hLUzt/OdBO2JB8vCSfGyeU4lYVlp9Ryeu72hKnBdveXrS59uQdvWEu2jEB5Q47P5xUztXlhWhSctmG3WzpCyaVxzoUwRfHldDm9vKZre2JsJCtPoCW5xiQ5wCQEhHW+d7UMdTM8uI9VeO3r+5mf3uAmWPzWLJgDHd0tNPSdJBlhT6+XllGqdPORSV5/Hd9S0JWQ5Z5sK9tJzYtD5nvAAOzimlnsi6VZkhKcoZvXju/KJdbUnvVcCmCj5eOrCvb4sRwUpWkGlJy3eZ9vN3VR9AwUDBlEL47sZwb0iS7NvcGueK93WiGJCIlbkXgVVVeXDCVMce5auKfzZ18b2dDYoiIR1GYluPiiXmTD1kOWBsIc9H6XYR0Ax1zJ+dSBL+fPoGLSvKRUvLXpg5+W99KpxbjVJ+HyR0xXlrdSEjTObe6lB9cNI0x+amDUp5s6eLbO+qTZhvYgLm5HlbMn8p17+/llc6elHr/H00s59/GlWAbYvsDjW38e+2BROzfLkw782wq+XaVWTnujCGA21ds5f639ic5Bpsi+NeNS6guz6U3pvPzvQd5vLULKeGy0nx+OKkiMYRle1+I2/c0saY7gLM9QqdXQSrCXGB1s9TUsaEdpTeGyLFz7TmTuO2M1FnQQ5FS8vPnd/DA2/tRFEFUM4iMcRObamopIQTKwSC5tb1s+Pfz8QxRXe3UYnx9Wx1vdPaiAIUOG3fXVLKs0JQKuepP77BudycSM68fm5qLMSFnIEQlJTOiCi9fmNoX8ufGNu4YNCLVLswGvVdPq6bUaedne5r4Q2MbkXifiX13D+r+PhyqgiElkSG9AC6bwtI5FXz6vElMcjupHCaf9aeGVu7Ye9A8kWB+9j47pojbpxxdMtji8LH6FOK82N7NV7fWERgiy+xUBGsXTqfUmdy4dcHanWwekgRTMReX38+oOlKzD0lQN5j51paUcZFuRXDb5LFcO4xsA8DnNu9NuwMvd9h5b/H0o4qzSim5bU8T9x9oNwfeS6h0O/j7nFMod9rxazE+8/5etvWFTBEzQ3JlWQG/mjY+o75+b0w3RdUUhdpAiJ/va8YuBDpQ4bDzyJxJaRcbKSV/X1PP3S/X4g9qzByby62Xzjyi0MHUx9bQk29Pjv1Lia0vxqrzZ1Puso+4Ka6fxq4gq/Z08NN/bccf0swEvFMFzUDoEo9D5bmbzmJCUfJJdX97gOvuX0NLOIpiU9BDMf7vxTV8dlEVGxv8XPOHdwgPCRsZLoXokrLEacSlCN4/cya5Q/o10r2v7AK+MK6En0weC5izC55p7UYRcFlZPrkavLW7nVyXjb5wjJ8+t4NAJIYUUHhmBQddAqciiEjJsgIff5hRhStDnmN3MMyTLV1EDcnFJfnMzR3QOZJSsmZfJ2/WtlOU4+CyuWMp9I5+yWpMN7jn9T38ZdV+esMxFlQV8ONLZlBdfnTih6OJ1acQ59m27hSHAGBD8GZXb9L0o0BMZ3sgtSpCB1amkXU+lmzoCaSVEAoZkqda/Yd0Cqv9gbRhlU4tRrsWy9i13Bqfa1DpcmRcwIUQ/MfksXytspT3eoKUOe3MHrSbz7fb+Nf8qWzvC9EQjjIjx51WTvpgJErUkFS6HPhsKheV5LOqq49f7GsmbMiE2um+UIRrNu3hr5PGU5LrIneQtIUQguVnTGD5GRMS12mG5NWOHnp1g0X53hGPeOzJtaUmg4Ug5rWhaAZ2d/rXI6YbGBIcNoX3e4P8q7UbVcBlZQVmHsehMrbAjT+kmTLPgxr7DCkp9SWHXaSUXPvn1TT6Q2aESJgy5Xc+u4PpY/N4fENjikMAEGEDpS1iJp4xT1y7AmEW5A04nNpgOG2+W5OwotXP/FwvZxbkMNPnYeYQUbpPLRif+HlBVSFv1razyqbxXKAPrSNMrE9Dem28LiW372nizqkDu39T6dXAaVOZ7HHx3Ymp4m+6IfnUvavYUO9PvHfv+Nd2HvjcaSw9zI7kY82PntjM05uaEh3Tb+/u4Mp73ub5m5YyvvDEi2NKKakLR3ErCmXOwxtrOxJOKqeQoyookCJ8JgQp7fU2RSCSZMUGcB9GK/6R4FGUtOJsAL40onVDKXLY6ErTECWAnDQKls0RjS9t3cf7PSEUAXk2G7+pqeSswsw7oRKHnY8MM2GsJsdNTZo5vXWhCF/asp+dwTAifj/3TJ/Agjwvf25sS2m6M4C9vWEufnA1skfjktkVfPXsUzjgDzG5NAfFbeORg500hKNMcDu4r6E1EbrSDMl3qso4Iz8HA1iQ682Yk1Fl2jHJACz52SuU+1z86OJpXDrX3E37g1FueWILL25rRjeguMRN61QfUa8NBfj9q7tR9/bitqnoaTYibrvKFaePY02fKUUx3uVgVyDMWw2dtMU0ItPzMSo8iKCGur+PYHuYX72wkzQCGAMMcjialFTEF4wD/hAPrdrPpvZewuMcaTPZByMa39pRjyYlnxtTjI5EQXBlWUFiN28Ykh8+vpmnNh7Apgo6zyjG/l4n9mAs0R9huFQeXmhwx5SxhDWD21Zs5fENB9B0g6ll5syI+RNSCxjufW036+v9SdfphuQLf1nLjtsvMudYjwKtvWGe3NhkNk8OIqIZ/PHNvdx22cwTas/bXb18Y3s9XVoMXcIsn5v7ZlQd8RyPdJxU4aOtfSE+tn5X0mxXAJcQXFicx1iXgytK81ndE2Bdd4CtfSH2BiNJncAuRfC18aV8/zhK3RpSsuCdbTQNSei6FcEDsyYmYsuZ+HtTBz+qPZAUJnApgstLC7i7Jjl5LKVkyeod7AtFkhyRS8BrZ9QcWc9DBmKG+bxao1rSY3lVhXfOqOH6rft5tzuQekPNwL6xA7UzmnDTNkUQy7ejzS9GVZVhK1hMmXDz648zqlgad3ZdWowHGtt5pbOHza29ROyKWakT1VEbg4geDRSJ7aDZDOi2q/z20/M4d1opF//3m+xu6UMb9F6SNkHkrDKU3hj2DR1JTWPSJsyTSNRA2ASFk/PpqPLgUBSihsStCsK6gYJIyHKojQFsO7sTuxhVQJHXQVtfavOgFKDV5GGMz0EBJnuczM/14tUk/3hyO1pIx5AQXVCMUTCyEtn+nNtXxpfyg0kV/H1NPbc+s5VQfMccG+sxZy4MeumlAKPMTd1N5/CFB9fy5u52YoPKWl12M2Q2cYi43Gl3rEz7vAAKPHaqy33ceO4UFg/SHnqhvZvf1LXQEo2xOM9LdZfOM+saCURiXDijgq+dcwr5nqNbLN/d28GXHlpHbzhVD2DOuDye+vqSo7r/w6EhHOXs1TuSPteqgHFOB+8srBl2/OlQrPBRnBk5bn58yhhu3dOEXQikNJt0EPBkmx8b8LuGVhzxgR4OYc4rdinmkI+YlCwp8PHNquOrgaIIwcOzJ/HJjXsIx98AmiH58viSQzoEgKsrCqmPRPl9fSv2+HO5oCiXu6amJvTWdgeoD0dSTiZhaSYlj2US8JVOs6Fs6GPFDMn/NndyVoEvvVNQQOk2HWT/8qIZksisAlBE8jSxNJinD/NvPrd5H2sWTUcRcN7anXRqMVONNF7PL3o1HGvazBJdI/mcGNJ0/t/KXfhcduo6gkkOATBVUw8EUbqjSU1j0qkQWVxqxvvjh8ym+JOJxB1AJNHFN2g+w87u5J4EaUo7p0URZr4C04fsCUbYFTSb3OTCUhxr2lD6Ytg3dRCdU4gscB7SMRjx1+6ehlY+WV7Ig+/sTzgEwOwTGaomLkFtCdHQEeSN3e3oQ/ocwprO71/fwy8/MTvp+uAwfQ5dQY1393ayqWEdP//ELC6dO5Y/NrQmybk8vq4FtTmU6Kt4YNU+nt1ykBe+ufSwBQoHM6HIk3JKAFNB9kTnFB460I4mk23RpTke+B1/X2Lu+dFyUjkFgM+PK+HysgLe7OrltY4enmj1J04O/XuB/l1n//cxTgffm1hOTY6Lad7UkMjxoCbHzcbFM3jL34tf01mUnzPi+KEQgu9PrOBr40vZG4pQ4bRnjK3vCISTKoUGs9qfZoE+ClqiWtoFPCIl9aEoef3Nc7ocGKQSl7IQQxYX6VGTyzBHiIHkydYuWiIaHYP0hxLiejv8EBvoxhi6bNZ3BtnfEUg740UYplMZfHsA7RSfaetIQiCaWS+mdETiNiU/ULq2BAmgCIzigfxE/xIrVQEKaDMLcL7bhtAkznUdGE6F6LKRnXYNaRZpNAeGOKQMMU4FeL+lh5hI33PxVkPqIKJTK/N5s7ZjWDtCms6tK7Zx3oxy7trbnHAIIhRDORhMskfTJR19Uf65vpHrFlcNe7/DUZHn5pxppby2ozUpl+O0KVy/9NCVaMeShnA042e1eRilgcPlpGxeK7Tb+FhxPlv6QimhpHTUhSKcXeA7YQ6hH1tcTvjysoIjSijl2FRm+zzDJltjw+yy0+nJjBQpZcpOOlM/iFdRWFSQw5puswFKqetFdEZQmkM41nVga0htjBIGmeeEDkPEkHRFY6zs6EkNOUmJEg9RZWJqmY9pGXaIUgGZ58Aod5ulrXGMYteIO5pFT1xaYoR/LxWzazm6oDjzbYRA+uxJU9REJFPWKhVFmH0SepkrScIkXcZNEbBkcjF6jj1FcwniYa7c1PfjHZfPGlHeoC8c472O3qSnKrq1tI2MIU3n7d3th7zPQ3H31XP51GnjcdkUFAHV5T4e+vzpTC49+rkSh8OZ+Tl40lTA6VIyb5heq8PlpHMKtYEwl2+opfL1TWzpG5lwnA7MeHsLp67aekxa8rOJqV4XtgyfxcHlgiPFkJL/rmth2ltbqHx9E6e/s43n2swE4owcN8sKfUmdwE5FMNZl55KSPMa7HCiAEpM41rXjeL8LxZ8+XCLCOqIvllHbJxNuRWFpoY+iTA2Iw3wiXHaF7320mtnj8pk9Lg/noJOKEIBNwT7Oi32sF3LtOOK/F9rIF2DsCkpbCKMgvSMfunBq1blEzi5HplloUxj8UmXo2M7EJSX55E7NR7pUpDrk7uIvg8ehku9xcOcVs5henAPlniTnKOOPO3dWavh1QpGX529awqnj87GrIrN/Ayb4XESHhOfSYVPEMakOctlVbrtsJttuu5Adt1/EC99cyoKqEz8k5xPlhZQ6bANjSTHzZR8rMScpHitOqvBRRzTGJRtq6Ynpw9VwpEUCTfEKDY+qJCpvArrOyx29BHWdZYW5lB+HErHjSXlM4NndSzAUMwfTl5q7WhV4stXPM23dXFaazy2TKjJ2cq/q6uOne5vYFQjjUpSkSW714Shf3VbHQ7NUlhb6+OOMidy1sY5H1zcQixmcO6OM786s4slWP1O9ThwCwlU5piKoZiTF1N12QWjQ+dm+qZPoacXYnCr2uALpwjwv41wO6kNRdgbDtEdjiVCKWwhqclw82txJjqrgFGZtfQIDjDwHSlfqaaHQa+e3nz6VhfHB7Q/+2+n86sWd/HN9I1Hd4JzqUr54/mQ2xaLYhOC8RTWs2dnOC1ubqY1INutGckfzoLCVCokmQ+mzYd/ahR5woc3Ix77Vb3YoG2BXBVfOG8vTmw4muqXVrijGGA8ZPTuY+ZGOSGLnLjGF9PpxClhakIvHplBgU/nbwQ7s8R2pLiV3T6uk1GlneWUJ/7lEQ2sMoHREkG4VfayXsqDBpS4v1eU+Lps3NjGPY9rCMWzb3AJ1AYhJjEIHak0+35yWXlV1Slkuj99wJgBPb2riB/98P3nQjU3hyvnjGO91cU6hj9c6e4lIicx3IF1qQo+pH7uqcO3CCRwrFEXgGEXVVI+q8PyCqfymrpUVbX7cqjlq9tr4pMJjxUlVffS7uhZ+ub85OWRkSDNM0R4Gl4oxzovIsaNCUtfuYGq8Ll49fRpvd/Vy3eZ9/XeDLiXfm1jO1yd8MIZxPLf5IN96dCOaHpdIVgX47EROK0ZRRGIxdQhBldvBq6dPQxVmdcxjzZ283mWK1q3s6DGTtcMwJ8fNC6dVc+/re/j1S7uIxMz6flGVQ3hqbmIHLDDnKutRA72uF68/So7XQSxmML7Ig781SFNLAENKFCGYMTaPr141g05DZ36ul2qvi3vqW/nFvoNEDImBuZEtsquU2W3sCkUTDkuNP55bVdDCGsaqNkRUT0owO20Kc8bl8ZfPn57SeTxSpJQsf2MHr2lh842iCApicNGEQvaEosz2uVlWmMtTrX7qQhHmu5xseqORzY1mz4OqCK6aP46vnD2ZslwnP3piM0++10RY01EVQWR6HtoYTyKEIgCHMAfeCwSxoIZzbXtCssNT7KZzVj42u4JNCO6cMjZpPGR7NMbLHT0owpSnKIhvBiKGwTUb97CpL0RYN3Cr5u2fmDeZ6fHy48auIH9bXc++9gAzK/N5xa2zNmA2MrpVwX9Wj+eikpHJWtz3xh7ufqkWgVlYcOmcMdx5xUycNpVATOcb2+t5qaMHuyJQIjpjtvXQ3BZEEQKfy8avPjWHs6aMbo9DtmJ1NMe5YVsdjw0O/8QMHKvbUEI66BJVMXcXP7hiJmqZm5trU6d+gVlCueXMmcx6e0tiAEk/bkXw+LwpzDuC0MuJJKzpzL9jJYFIctWHECCrfISn+JLitF5V4Z7pE1iYn8OF63bRHG90GylCl1Q1hDjYHkR2RBCA7rWhnVmaEg+2CVhx6hTCoRjL730HGTVAl0glPgDlwilM87ipLveldC8/1+bnC1v2p+RAnfEqrKH/ThVztvN/PLGF5n3dyeWVgCvfwc4fXjDi55mJmG7w2PsHeG5HK9WlOXxt0STyPMOfKtt6I/RFYkwo9KTo+m9s8PPSthbcDoVL54wl5FB4tt3PWKeDy8ry2dYXZmtfiEqXg8X5XjY2+KnrCDKtPJfpY3LpiMboisWY4HKOWE8LTAf3tr+Pdd0Byp12Pl6Sn5hyt3Z/J9fdvwZNN9B0iduukO9x8JevLER1qlS5naiH2U0f1nQO+EMU5zjJc6e+Xp1ajE5t4Hm09oQJRnUq07xmFgNYJalx5vjcPDtICE5tCCCCsUTVgm6Abhjc/cw21txyPnftPZi2CWyyx8lrnem7miOG5H8PdmS9U9jU4I835yUjJch9vdjCMWKzBiachXSDrX0h3usJciAcTQ67jITuKE07u0AVGPkOhD9KbFL6RF1Mwjv+Ph57ZR9GWE8s1GYoSXL/a3upveUClCFJt9/XtyQNgh9MJnt1zJK+lvqe1PJKINwdpSusUeA68rBgIBLjk/e+Q11HgEBUZ7Vd4W9v7OeR6xcOK8lR4nNS4ksfK547Pp+545N33FNzygd+n+tJygnNn1DI/AkDp4Eih42iIzj5CCFYUuBjyZDyRykl33l0U2KGBEBIM4j1Rvjr6/u4/fIja/Jy2VVOKcmc0C202ygcFNYszR1emM/i0JxUiearywvxqGriSavNoVQ9fsyyv53NvfxgYkXKXAK3Irhl0piM4RIDkpQ3sxWnXU0rZQzx8ZmtYZT2gUEsblVhotvJM23+w3cIuoG9tseUhdYlSm/UrNDxZl6UNveG2LPPn7JQA8RCMbZ3JlckdWoxfr6vOXMT2zA27w1G0lav9GM/yk/Jva/vYU9bH4H4ghnSDHojMW76+3tHd8dZRGtvhJae1MINzZC8uK15FCyyOFJOqpNCnt3G8wum8uPaA7za2YOwpZ+GZRimWNnnSvPxqgq/3N/MwYjGZI+TH58yhqWFPjqiMbR0IwBVhUs/AFLAs8fm4XPZEwvVUIQuUZqCGCUuVMyZDBeV5HFvQ+vIH0RKRK+GbWd3UhWR0EGEYyi9MYzc9B2n83I9vGAT6KkDwkCCz5Es17HGH8AhBJHhSggGj6ocxIJcL6uri9iyrS1pkyAFFFXkkJOhpHdncy+PbWgkFNX56IwyHDaFZzc3oyqCK+aNTZwCntp4gEiaBoPGrhAHu0NU5B3bUuegbvBkSxfregJM9ri4urzwiE4Fh4PLlnmTMXS+hEV2k3VOQQhxIfBrzHDvn6SUPzuW9z/e5eCBWRMBWFHQxPf+kVzhIARU5LsSR9ZPVhTyyYrU8rMih41bTxnLT/YcQBskb31OoY/zig7ddTzaKIrg/s+dxifvXZXRMSiKGd9flJ/Df02rxKkofH5cCT/c2ZiUTxCYR05VCOyKwC7MHWK0M4qyrj2l8QzMMISvMUj3GE9Kv4ENuKaiiHfmlPPKuweSu4OB3BIPlbnJC2meXU3vDqQECUpdnykvPeSxvKrCecW5nH7lXJY2vUmwO5JwHnaXyt8+kzbsyoOr9vGz53agxQx0CY+sqUMiMAyJEPDw6jpuWDaZb5w3ZVj5gcONsR+KtqjGRet20anpBA0DlyK4e38zT506Ja0W1bEiz2NnQVUha/Z1JuYxgDkW89pFVcftcS2OPVmVaBZCqMAu4AKgEVgLLJdSbkv394ebaB6KlJKfPL2Vv69twKaBDwwLAAAKmklEQVSY7Zc5ThuPfGkhk4aJYw5me1+IR5s76dMNLi7OY1mh7wM1ArAnpHH6nS+lKG+67Sr3/J/5LJxUlCSDLKXk+zsbebSl05QKAYrsNh6dewo+VSXPpqIIWOXvY2dviNv+tD55UA1ml+2kOSV8Y3IFnQU2bq1rNtdhzNryh2ZN4qxCH2FN5+w/rqKlsWeg49ht45mvLqamKPn/o0vJ/FXbaIlqyc7BkNg3dKB2RIhVeolNzcOmCmyKwKEoPDJ7EvPjSqJSSh7e2sS7DV1ML/Vx/dzx2NKIH7b3RTjzZ6+k3f0PxmlTeOnbZ7Pi/SZ+/XJtQmUTzKczvSKXf9141rD3cbh8e0c9jzZ3psy+np3j5sXTqo/pYw2ltTfMZ/64miZ/CATEdMlHZpRx99XzRk3QziI9H5jqIyHEIuAnUsqPxi/fDCClvCvd3x+tU+inoTPI+rouinIcLD6l+KR7A7+xq40v/3U9YC6uArh24QRu+VhNRgdXH4qwoSdIqcPOwnxvxt3wzav38Lend5oXDHMHbqtws+nLZ5ETD2n0xHTe6OzFoQjOKvClqNC+Vt/Jyr3tVBd7+ez0ipQEcz+7AmGu2bSHnpgOEvo0HdsOP7bGgfyD3aXyg2vnUpXvYWlBzmHPSAB44r1G/v2JLRlPWP04bQo/uriGa04fz789sJaNDX403cBhU3DbVR798qIRbz5GSs2bm9MWR9iEYPuSmSNS2T0apJRsqO/igD/MrLF5KcJ3FtnBB6n6aCzQMOhyI3DG4D8QQlwPXA9QWZk6LvJIGF/oGRVd9Gxh6dQS3r35PF7Y2kxfJMbZ1SXDVnwAVB5iylY/d51xClecUsItb+3GH9T46NQS/uPUiUllkLk2lUuGycMsqyxkWeWhO0inel2sWzSdDT1BemI6e3d18svmZog3tgnge+dN5YunlB/qrobFoaojkthQFIHTpuC0qTz8xTNYX9fFxgY/FXluzp9eivM4LNCZy0vlMQ9VpUMIEa90Ou4PZXGcyDankO5dm3SUkVLeB9wH5knhRBh1MpDnsfOp08Yf+g+PgNOLc1l5+anH5b6HogiRGCxz7qJcLqop44UtzUjgI9PLjonzX1ZdMlwxUwIpJR+ZYTogIQQLqgqPuzzC8vJC/tDYltSgaQPOKvClzAyxsEhHtjmFRmDwyjSOuMqwhcWRMDbfzeeXTDym9+l12vjDtfP58l/Xm81+EiKajhACh00xG/Ok5O6r557wcZLfqipnXU+Q93qCyPjpoNRh59fTjs2p2uLDT7blFGyYiebzgAOYieZPSym3pvv7Y5VTsLA4EvoiMV7Z0WomxKeWoCqC13a2YVME50wrTduBe6J4ryeY6GheUpBzWANYLD78fGByClLKmBDi68ALmCWp92dyCBYWo02O08alc5LF3a6af+yGEh0N83I9Wd9Vb5GdZJVTAJBSPgs8O9p2WFhYWJyMWJknCwsLC4sEllOwsLCwsEhgOQULCwsLiwSWU7CwsLCwSJBVJamHixCiDag7jJsUA0c/yfv4kK22WXYdPtlqW7baBdlrW7baBUdn2wQpZdqxdB9op3C4CCHWZarNHW2y1TbLrsMnW23LVrsge23LVrvg+NlmhY8sLCwsLBJYTsHCwsLCIsHJ5hTuG20DhiFbbbPsOnyy1bZstQuy17ZstQuOk20nVU7BwsLCwmJ4TraTgoWFhYXFMFhOwcLCwsIiwUnhFIQQFwohdgohdgshfjjKttwvhGgVQmwZdF2hEGKlEKI2/r1gFOwaL4R4VQixXQixVQhxUxbZ5hJCrBFCbIrbdmu22Ba3QxVCvCeEWJFldu0XQmwWQmwUQqzLFtuEEPlCiH8KIXbE32+LssSu6vhr1f/VI4T4ZpbY9q34e3+LEOKR+GfiuNj1oXcKQggV+B1wETAdWC6EmD6KJj0IXDjkuh8CL0sppwAvxy+faGLAd6SUNcBC4Ib465QNtkWAc6WUc4C5wIVCiIVZYhvATcD2QZezxS6Ac6SUcwfVs2eDbb8GnpdSTgPmYL52o26XlHJn/LWaC8wHgsATo22bEGIscCOwQEo5E3OswDXHzS4p5Yf6C1gEvDDo8s3AzaNsUxWwZdDlnUBF/OcKYGcWvG5PARdkm22AB9iAObt71G3DnA74MnAusCKb/p/AfqB4yHWjahuQC+wjXuSSLXalsfMjwNvZYBsDs+sLMccdrIjbd1zs+tCfFBh4QftpjF+XTZRJKQ8CxL+XjqYxQogqYB6wmiyxLR6i2Qi0AiullNli293A9wFj0HXZYBeY881fFEKsF0JcnyW2TQLagAfiIbc/CSG8WWDXUK4BHon/PKq2SSkPAP8J1AMHgW4p5YvHy66TwSmkm0No1eFmQAiRAzwGfFNK2TPa9vQjpdSleawfB5wuhJg52jYJIS4BWqWU60fblgycKaU8FTN0eoMQYuloG4S50z0VuEdKOQ8IMLrhtRSEEA7gUuAfo20LQDxXcBkwERgDeIUQnz1ej3cyOIVGYPygy+OAplGyJRMtQogKgPj31tEwQghhx3QID0spH88m2/qRUvqB1zDzMqNt25nApUKI/cDfgXOFEP+TBXYBIKVsin9vxYyNn54FtjUCjfGTHsA/MZ3EaNs1mIuADVLKlvjl0bbtfGCflLJNSqkBjwOLj5ddJ4NTWAtMEUJMjO8ArgGeHmWbhvI0cF385+sw4/knFCGEAP4MbJdS/r8ss61ECJEf/9mN+SHZMdq2SSlvllKOk1JWYb6vXpFSfna07QIQQniFEL7+nzFj0FtG2zYpZTPQIISojl91HrBttO0awnIGQkcw+rbVAwuFEJ745/Q8zOT88bFrNJM5JzBRczGwC9gD3DLKtjyCGRfUMHdNXwCKMJOVtfHvhaNg1xLMsNr7wMb418VZYtts4L24bVuAH8evH3XbBtm4jIFE86jbhRm73xT/2tr/vs8S2+YC6+L/zyeBgmywK26bB+gA8gZdN+q2AbdiboS2AH8FnMfLLkvmwsLCwsIiwckQPrKwsLCwGCGWU7CwsLCwSGA5BQsLCwuLBJZTsLCwsLBIYDkFCwsLC4sEllOwsDhChBBXCCGkEGLaaNtiYXGssJyChcWRsxx4C7NxzcLiQ4HlFCwsjoC4RtSZmM2H18SvU4QQv4/r3q8QQjwrhLgq/rv5QojX4+J0L/TLE1hYZBuWU7CwODIux5wJsAvoFEKcClyJKYs+C/gipmx7v6bUb4CrpJTzgfuBO0fDaAuLQ2EbbQMsLD6gLMeUzQZTDG85YAf+IaU0gGYhxKvx31cDM4GVpnQNKqbUiYVF1mE5BQuLw0QIUYQ5VGemEEJiLvISU4k07U2ArVLKRSfIRAuLI8YKH1lYHD5XAQ9JKSdIKauklOMxp4m1A5+I5xbKMEXywJyQVSKESISThBAzRsNwC4tDYTkFC4vDZzmpp4LHMAegNGIqWf4Bc3Jdt5QyiulIfi6E2ISpQLv4xJlrYTFyLJVUC4tjiBAiR0rZFw8xrcGcftY82nZZWIwUK6dgYXFsWREfCOQAbrccgsUHDeukYGFhYWGRwMopWFhYWFgksJyChYWFhUUCyylYWFhYWCSwnIKFhYWFRQLLKVhYWFhYJPj/e/xn5aro9p8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', c='survived', cmap='tab10', data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Still not great, so we're going to create a `ListedColormap` so we can set the colors manually. We get the [listed colormap](https://matplotlib.org/api/_as_gen/matplotlib.colors.ListedColormap.html) from the [colors module](https://matplotlib.org/api/colors_api.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.colors as mcolors\n",
    "cmap = mcolors.ListedColormap(['black', 'yellowgreen'])\n",
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', c='survived', cmap=cmap, data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's add a legend"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "We can't just use the label parameter here because we get one label per call of the `scatter` function and here we need multiple labels. Instead, we can make use of the fairly new [scatter legend](https://matplotlib.org/3.1.0/gallery/lines_bars_and_markers/scatter_with_legend.html#automated-legend-creation) functionality to generate a label based on the colors. Here we assign the output of ax.scatter to the `sc` variable because will need to use the sc object to generate the legend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "sc = ax.scatter('age', 'fare', c='survived', cmap=cmap, data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n",
    "_ =  ax.legend(*sc.legend_elements())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Lets add custom labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "`sc.legend_elements()` returns two lists:\n",
    "* handles: plot objects displayed in the legend (in this case the scatter points)\n",
    "* labels: the label attached to each handle\n",
    "\n",
    "In  this case, labels are 0 and 1 because that's what was passed in as the color, so we overwrite the default labels with our custom ones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "sc = ax.scatter('age', 'fare', c='survived', cmap=cmap, data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n",
    "_ =  ax.legend(handles = sc.legend_elements()[0], labels=['Died', 'Survived'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "## Pre Matplotlib 3.1 version\n",
    "\n",
    "Scatter's legend_elements() is a new feature in Matplotlib and so may not be on your computer. Another way to set the legend would be to segment the data and use the label parameter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "_ = ax.scatter('age', 'fare', c='black', cmap=cmap, data=df[df['survived']==0], label='died')\n",
    "_ = ax.scatter('age', 'fare', c='yellowgreen', cmap=cmap, data=df[df['survived']==1], label='survived')\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n",
    "_ =  ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's clean up a bit because large dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Lets add some transparency using the alpha keyword because there are a lot of dots. Then we set the border of our dots to black to get some definition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "sc = ax.scatter('age', 'fare', c='survived', cmap=cmap, alpha=.5, edgecolor='black', data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n",
    "_ =  ax.legend(handles = sc.legend_elements()[0], labels=['Died', 'Survived'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Encode even more information: Bubble Chart"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Is there a pattern in age and fare and survival...and the passenger class? We can encode one more variable (in this case `pclass`) as the size of the point. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "sc = ax.scatter('age', 'fare', c='survived', cmap=cmap, alpha=.5, \n",
    "                edgecolor='black', s = df['pclass']*25, data=df)\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n",
    "_ =  ax.legend(handles = sc.legend_elements()[0], labels=['Died', 'Survived'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Visual Overload: markers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "We're not done yet, because we can still encode the shape of the point! Here we have to use two seperate functional calls to scatter to set the markers. Lets see how sex (as recorded in these logs) factors into survival rates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "sc = ax.scatter('age', 'fare', c='survived', cmap=cmap, alpha=.5, edgecolor='black', \n",
    "                marker='s',label='Female', data=df[df['sex'].str.match('female')])\n",
    "sc2 = ax.scatter('age', 'fare', c='survived', cmap=cmap, alpha=.5, edgecolor='black', \n",
    "                marker='^',label='male', data=df[df['sex'].str.match('male')])\n",
    "\n",
    "_ = ax.set(xlabel = 'Age', ylabel = 'Fare')\n",
    "_ =  ax.legend(handles = sc.legend_elements()[0], labels=['Died', 'Survived'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Putting it all together: Information overload\n",
    "As a reminder, these are the variables in the dataset:\n",
    "* categorical: 'pclass', 'survived', 'sex', 'embarked'\n",
    "* quantitative: 'age', 'sibsp', 'parch', 'fare',\n",
    "* qualitative: 'name',  'ticket',  'cabin',\n",
    "\n",
    "Create a scatter plot exploring the relationship between:\n",
    "1. family size and fare and age and survival\n",
    "2. can you throw in an additional variable?\n",
    "3. what interactions are you interested in unpacking? post your figure to the slack"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Seperate a bit, but interact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "At a certain point, there are diminishing returns to trying to to cram more information into one scatter plot. Instead, matplotlib supports linking two plots together via the sharex/sharey parameters to `plt.subplots`. Here it's used to link two plots, one for each sex. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: Cannot change to a different GUI toolkit: widget. Using nbagg instead.\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"\" width=\"432\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib widget\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)\n",
    "x, y, c, s = 'age', 'fare', 'survived', 'pclass'\n",
    "\n",
    "_ = ax1.scatter(x, y, c=c, cmap=cmap, alpha=.5,  marker='s', data=df[df['sex'] =='male'])\n",
    "_ = ax2.scatter(x, y, c=c, cmap=cmap, alpha=.5, marker='^', data=df[df['sex'] =='female'])\n",
    "_ = ax1.set(ylabel=y, title='male')\n",
    "_ = ax2.set(xlabel=x, ylabel=y, title='female')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Putting it all together extra: Dashboard\n",
    "\n",
    "Create an interactive dashboard that combines the figure above with a broken out version of your information overloaded plot."
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
